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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

A Single-Lap Joint Adhesive Bonding Optimization Method Using Gradient and Genetic Algorithms

A natural process for any engineer, scientist, educator, etc. is to seek the most efficient method for accomplishing a given task. In the case of structural design, an area that has a significant impact on the structural efficiency is joint design. Unless the structure is machined from a solid block of material, the individual components which compose the overall structure must be joined together. The method for joining a structure varies depending on the applied loads, material, assembly and disassembly requirements, service life, environment, etc. Using both metallic and fiber reinforced plastic materials limits the user to two methods or a combination of these methods for joining the components into one structure. The first is mechanical fastening and the second is adhesive bonding. Mechanical fastening is by far the most popular joining technique; however, in terms of structural efficiency, adhesive bonding provides a superior joint since the load is distributed uniformly across the joint. The purpose of this paper is to develop a method for optimizing single-lap joint adhesive bonded structures using both gradient and genetic algorithms and comparing the solution process for each method. The goal of the single-lap joint optimization is to find the most efficient structure that meets the imposed requirements while still remaining as lightweight, economical, and reliable as possible. For the single-lap joint, an optimum joint is determined by minimizing the weight of the overall joint based on constraints from adhesive strengths as well as empirically derived rules. The analytical solution of the sin-le-lap joint is determined using the classical Goland-Reissner technique for case 2 type adhesive joints. Joint weight minimization is achieved using a commercially available routine, Design Optimization Tool (DOT), for the gradient solution while an author developed method is used for the genetic algorithm solution. Results illustrate the critical design variables as a function of adhesive properties and convergences of different joints based on the two optimization methods.

Smeltzer, Stanley S., III↗
DOE OSTI2026

A Catabolic Powerhouse for Biorefineries: Characterization and Engineering Erwinia spp. Strain LJJL01 to Produce Bioproducts

Nonmodel microbial hosts can efficiently biotransform unconventional organic feedstocks into advanced bioproducts, leveraging their superior metabolic capabilities and resilience to process-relevant physicochemical conditions. In this study, we domesticated Erwinia spp. strain. LJJL01 (Er LJJL01) as a potent microbial chassis to advance the emerging biorefinery strategy for the valorization of lignin-rich biomass and plastic, thereby enabling the circular economy. The strain exhibits remarkable chemical tolerance and can biofunnel various substrates, including sugars, acids, polyols, and aromatics, in minimal salt media to produce native fine chemicals such as acetoin, 2,3-butanediol, and lactic acid. As a proof of concept, engineering this strain with advanced genetic tools enables the production of tailored high-value chemicals, such as cis,cis-muconate from plastic-derived terephthalate and polyhydroxybutyrate from lignocellulosic hydrolysate. We established Er LJJL01 as a potent microbial chassis for the green synthesis of bioproducts from unconventional organic feedstocks.

09 BIOMASS FUELS↗
DOE OSTI2024

Optimization of electroporation method and promoter evaluation for type-1 methanotroph, Methylotuvimicrobium alcaliphilum

Methanotrophic bacteria are promising hosts for methane bioconversion to biochemicals or bioproducts. However, due to limitations associated with long genetic manipulation timelines and, lack of choice in genetic tools required for strain engineering, methanotrophs are currently not employed for bioconversion technologies. In this study, a rapid and reproducible electroporation protocol is developed for type 1 methanotroph, Methylotuvimicrobium alcaliphilum using common laboratory solutions, analyzing optimal electroshock voltages and post-shock cell recovery time. Successful reproducibility of the developed method was achieved when different replicative plasmids were assessed on lab adapted vs. wild-type M. alcaliphilum strains (DASS vs. DSM19304). Overall, a ∼ 3-fold decrease in time is reported with use of electroporation protocol developed here, compared to conjugation, which is the traditionally employed approach. Additionally, an inducible (3-methyl benzoate) and a constitutive (sucrose phosphate synthase) promoter is characterized for their strength in driving gene expression.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Enhancing chemical bioproduction with rational control of bacterial post-translational modifications

Efficient conversion of inexpensive feedstocks to valuable chemicals by microbes is critical for a robust bioeconomy, but the ability to rationally design bacteria is hampered by insufficient knowledge of how post translational modifications (PTMs) control bacterial protein function and thus bioproduction phenotypes. Our study will focus on the lysine acetylation, a ubiquitous bacterial PTM that can affect the function of enzymes in central metabolism that are often critical for bioproduction processes, disrupt transcriptional regulation, and reduce translation. However, most lysine acetylation data is observational, which means that we do not know when, how, and what specific acetylated residues affect protein function and bacterial physiology. For our model host, we will use a Pseudomonas putida strain that we previously engineered to convert lignocellulosic feedstocks into chemicals such as itaconic acid (ITA). With this strain, we use a dynamic two-stage bioproduction process in which ITA is produced during a non-growth associated production phase. Production is highest during growth stages when lysine acetylation is low in other organisms (early stationary phase) and stalls in conditions where acetylation is highest (late stationary phase). The switch from high to stalled ITA production is also correlated with an unexpected increase in acetate levels – the precursor to non-enzymatic lysine acetylation. As such, we predict that lysine acetylation plays a substantial role in regulating the metabolic pathways required for ITA production. We will develop a generalizable approach that combines high-throughput genetic screens and cutting-edge genome engineering with state-of-the-art proteomics, metabolomics, and genetic code expansion methods to identify and modulate lysine acetylation patterns in bacteria. Ultimately, these strategies aim to manipulate protein expression and acetylation patterns to enhance bioproduction phenotypes (e.g., sustained ITA production in late stationary phase).

60 APPLIED LIFE SCIENCES↗
NASA NTRS2015

Life in the Clouds of Venus? An Experimental Synthetic Biology Approach

The surface of Venus constitutes the most hellish and biologically inhospitable planetary surface in our solar system, boasting a pH of 0, blistering winds that can melt lead, and pressures of 60 atm. However, during the earlier years of the solar system, without the runaway greenhouse effect that has plagued the planet, Venus potentially housed oceans and perhaps even life. There is a possibility that microbes could have retreated into hospitable niches in the atmosphere, as suggested by Carl Sagan as early as 1967 [1]. For example, 50 km above the raging hell of the Venusian surface, exists a relatively temperate environment that might serve as reservoir for life. This astrobiology project seeks to explore life at the extremes and to theorize whether microbial communities could not only survive but also reproduce in the Venusian atmosphere. Specifically, we ask: are aerosols viable microbial environments? But before we can test for life in the clouds, we have to develop a proper reporter to visualize cell growth in situ. For this purpose, we aimed to develop cell-growth dependent reporters to serve as remote biosensors for cell growth. We developed two using the polA promoter, a DNA-replication dependent promoter, and nrd operon promoter, a cell-cycle dependent promoter. Using these cell-growth reporters, the next step is to aerosolize microbes expressing these reporters in a suspension chamber adapted from a Millikan Drop Apparatus to assay reproduction in an aerosolized environment. Better yet is to test the reproduction of microbes in a microgravity regime such as on ISS.Approach: We engineered two cell-cycle dependent genetic reporters. One was the polA promoter which codes for DNA Polymerase I, a gene active in DNA replication [2]. The other was the nrdP. The activation of ribonucleotide reductase reduces ribonucleotides into deoxyribonucleotides and is involved in the bacterial cell cycle [3]. This promoter began activation during the initiation of DNA replication and is cell-cycle dependent [4]. These promoters were fused to a GFP reporter, transformed into E. coli. The constructs were deposited in the iGEM registry as K847210: Escherichia coli DNA-replication dependent polA promoter K847211: Escherichia coli cell-division dependent nrd promoter Results: Our constructs displayed fluorescence when transformed into NEB-5alpha competent cells. While nrdP-E0840 displayed sufficient fluorescence as verified by fluorescent microscopy, the original polAP-E0840 construct (which uses mut3b GFP) exhibited low expression; while fluorescence was visible under the microscope, the signal was too weak for the camera to recognize. The polA promoter was therefore digest-ed with EcoRI and SpeI then ligated into plasmid pNCS containing a RBS, Clover, and a terminator. Clover is a highly engineered green fluorescent protein that exhibits extreme brightness [5] Fluoresence time course data demonsrated that the genes were induced in a cell cycle dependant manner [6]. Our assays via microscopy and the bulk assay shows that our promoters are functional as cell cycle reporters.Conclusions: The application of such tools are widespread and not limited to astrobiology; nrdP could be used to determine doubling times empirically and could possibly extrapolate DNA content from intensity of signals expressed by polAP. However, we are pri-marily interested in its use in astrobiology.

Escherichia↗
DOE OSTI2024

Genetic modification of the shikimate pathway to reduce lignin content in switchgrass ( Panicum virgatum L.) significantly impacts plant microbiomes

Switchgrass (Panicum virgatum L.) is considered a sustainable biofuel feedstock, given its fast-impact growth, low input requirements, and high biomass yields. Improvements in bioenergy conversion efficiency of switchgrass could be made by reducing its lignin content. Engineered switchgrass that expresses a bacterial 3-dehydroshikimate dehydratase (QsuB) has reduced lignin content and improved biomass saccharification due to the rerouting of the shikimate pathway towards the simple aromatic protocatechuate at the expense of lignin biosynthesis. However, the impacts of this QsuB trait on switchgrass microbiome structure and function remain unclear. To address this, wild-type and QsuB-engineered switchgrass were grown in switchgrass field soils, and samples were collected from inflorescences, leaves, roots, rhizospheres, and bulk soils for microbiome analysis. We investigated how QsuB expression influenced switchgrass-associated fungal and bacterial communities using high-throughput Illumina MiSeq amplicon sequencing of ITS and 16S rDNA. Compared to wild-type, QsuB-engineered switchgrass hosted different microbial communities in roots, rhizosphere, and leaves. Specifically, QsuB-engineered plants had a lower relative abundance of arbuscular mycorrhizal fungi (AMF). Additionally, QsuB-engineered plants had fewer Actinobacteriota in root and rhizosphere samples. These findings may indicate that changes in the plant metabolism impact both AMF and Actinobacteriota similarly or potential interactions between AMF and the bacterial community. This study enhances understanding of plant-microbiome interactions by providing baseline microbial data for developing beneficial bioengineering strategies and by assessing nontarget impacts of engineered plant traits on the plant microbiome.

09 BIOMASS FUELS↗
DOE OSTI2026

Multisite Field Evaluation of Oil Accumulation and Agronomic Performance in Grain and Sweet Sorghums Engineered for Lipid Hyperaccumulation

Oil sorghum (OS) has been developed by engineering grain (TX430) and sweet (Ramada) genetic backgrounds to accumulate triacylglycerols (TAG) in vegetative tissues as an energy-dense feedstock for sustainable aviation fuel (SAF) and other biofuels. This study evaluated two TX430 OS lines (TxHO-2, TxHO-3) and two Ramada OS lines (RmHO-1, RmHO-2) alongside wild-type (WT) lines in NE and IL over 2 years (2023–2024) to quantify genotype × environment effects on agronomic performance and TAG accumulation. Across four environments, TX430 OS lines showed average TAG concentrations of 15.0 g kg −1 in leaves and 12.8 g kg −1 in stems, approximately 19-fold higher than WT. Ramada OS lines accumulated 26.1 g kg −1 in leaves and 12.3 g kg −1 in stems, approximately 25-fold and 13-fold increases over WT, respectively. OS lines in TX430 exhibited an 18% reduction in biomass (8.4 vs. 9.9 Mg ha −1 for WT), while Ramada OS lines had similar WT biomass (18.3 vs. 19.9 Mg ha −1 for WT). Among TX430 OS lines, TxHO-2 achieved the highest TAG yield (190 kg ha −1 ), while RmHO-1 led the Ramada lines (335 kg ha −1 ) due to higher biomass and similar TAG concentration. Enhanced TAG accumulation increased N, P, and K removal in TX430 lines but not in Ramada lines. Structural carbohydrate and ash concentration were unaffected. Overall, results confirm vegetative lipid accumulation as a viable strategy for high-biomass sorghum, supporting its potential as a dual-purpose feedstock for SAF. Future work should focus on minimizing biomass yield penalties and improving nutrient use efficiency in oil sorghum systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Prediction of non-intuitive metabolic targets with bayesian metabolic control analysis to improve 3-hydroxypropionic acid production in Aspergillus niger

Development of efficient bioconversion processes is limited by the ability to predictably improve metabolic flux. Here we deployed Bayesian Metabolic Control Analysis as a platform to integrate multi-omics data with metabolic modeling and evaluated its ability to predict genetic interventions that improve metabolic flux. Global Metabolomics and proteomics data was collected from 17 Aspergillus niger strains engineered to produce the platform biochemical 3-hydroxypropionic acid from which seven actional genetic interventions were predicted from significant flux control coefficients. Of the suggested genetic interventions, two were present within the intuitively designed strains used for training (malonic semialdehyde dehydrogenase and pyruvate carboxylase) while five predicted targets were present within non-intuitive areas of the metabolic network including 5-formyltetrahydrofolate deformylase and four mitochondrial enzymes, alcohol dehydrogenase, succinyl-CoA ligase, aspartate aminotransferase, and malate dehydrogenase. Six of the targets were validated in the highest performing 3-HP strain used for multi-omics data generation which contained a prior disruption of the highest scoring target malonic semialdehyde dehydrogenase. Predicted directional perturbation of five of the six tested targets significantly improved titer and rate of 3-HP production and two significantly improved yield. The greatest improvements were observed following disruption of the non-intuitive target succinyl-CoA ligase which increased titer by 39% and yield by 29% (to 20.4 g/L 3-HP and 0.31 g 3-HP/g glucose) over the strains used for training. This study demonstrates the utility of Bayesian Metabolic Control Analysis and highlights the ability to predict meaningful genetic targets in unexpected areas of metabolism to improve engineered strains for bioconversion.

3-hydroxypropionic acid↗
DOE OSTI2025

Data for "Viral Delivery of Recombinases Activates Heritable Genetic Switches in Plants"

Viral vectors provide an increasingly versatile platform for transformation-free reagent delivery to plants. RNA viral vectors can be used to induce gene silencing, overexpress proteins, or introduce gene editing reagents; however, they are often constrained by carrying capacity or restricted tropism in germline cells. Site-specific recombinases that catalyze precise genetic rearrangements are powerful tools for genome engineering that vary in size and, potentially, efficacy in plants. In this work, we show that viral vectors based on tobacco rattle virus (TRV) deliver and stably express four recombinases ranging in size from ∼0.6 to ∼1.5 kb and achieve simultaneous marker removal and reporter activation through targeted excision in transgenic Nicotiana benthamiana lines. TRV vectors with Cre, FLP, CinH, and Integrase13 efficiently mediated recombination in infected somatic tissue and led to heritable modifications at high frequency. An excision-activated Ruby reporter enabled simple and high-resolution tracing of infected cell lineages without the need for molecular genotyping. Together, our experiments broaden the scope of viral recombinase delivery and offer insights into infection dynamics that may be useful in developing future viral vectors.

gene editing↗
NASA NTRSDate not supplied

Developing a Genetic Variant Calling Pipeline for Quantifying the Complex Mutagenic Load Accumulated in BioNutrients-1 Production Pack Samples

Microorganisms hold great promise for on demand production of labile nutrients and pharmaceuticals as well recycling and in situ resource utilization. The utilization of microorganisms for such tasks on space missions is hindered by the limited data on how microbes respond to spaceflight. For example, the genetic stability of microorganisms, and the genomic engineered traits added to deliver desired functions, over long-term storage in the spacecraft environment is poorly understood. The BioNutrients-1 (BN-1) mission conducted a 5-year study of desiccated storage in Low Earth Orbit (LEO) to evaluate the suitability of eight synthetic biology chassis organisms for long-duration space missions. We are employing high-depth, whole genome sequencing (WGS) to determine the mutagenic load that accumulated during long-term storage. Mutation analysis pipelines are well established for homogenous culture grown from a single colony, but the mutational landscape of the BN-1 samples present a unique analysis challenge, as every cell in the BN-1 samples had a unique genetic journey of DNA damage and repair. Consequently, sequence variants are expected at low allele frequency within samples. To address this genetic complexity, we apply two distinct computational approaches to identify mutations in pre-existing WGS data collected from populations of Chlamydomonas reinhardtii that were exposed to UV mutagenesis and growth in LEO. For reference genome free mutation detection, we utilized DiscoSNP++, which is a de Bruijn graph approach. For reference genome-based mutation detection we utilize GATK for Microbes, which is a Bayesian probabilistic approach. We will benchmark these approaches against the mutations originally identified using CRISP, a method optimized for pooled samples. Ultimately, quantifying the mutation load imposed by storage or growth on the ISS will help identify chassis organisms with both high levels of genome stability and viability, which are desirable traits for implementation of bioproduction in long-duration missions.

SNP↗
NASA NTRS2011

Evolutionary Computational Methods for Identifying Emergent Behavior in Autonomous Systems

A technique based on Evolutionary Computational Methods (ECMs) was developed that allows for the automated optimization of complex computationally modeled systems, such as autonomous systems. The primary technology, which enables the ECM to find optimal solutions in complex search spaces, derives from evolutionary algorithms such as the genetic algorithm and differential evolution. These methods are based on biological processes, particularly genetics, and define an iterative process that evolves parameter sets into an optimum. Evolutionary computation is a method that operates on a population of existing computational-based engineering models (or simulators) and competes them using biologically inspired genetic operators on large parallel cluster computers. The result is the ability to automatically find design optimizations and trades, and thereby greatly amplify the role of the system engineer.

Terrile, Richard J.↗
DOE OSTI2025

Recent developments of oleaginous yeasts toward sustainable biomanufacturing

Oleaginous yeast are remarkably versatile organisms, distinguished by their natural capacities to accumulate high levels of neutral lipids and broad substrate range. With recent growing interests in engineering non-model organisms as superior biomanufacturing platforms, oleaginous yeasts have emerged as promising chassis for oleochemicals, terpenoids, organic acids, and other valuable products. Advancement in systems biology along with genetic tool development have significantly expanded our understanding of the metabolism in these species and enabled engineering efforts to produce biofuels and bioproducts from diverse feedstocks. This review examines the latest technical advances in oleaginous yeast research toward sustainable biomanufacturing. We cover recent developments in systems biology-enabled metabolism understanding, genetic tools, feedstock utilization, and strain engineering approaches for the production of various valuable chemicals.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

RB-TnSeq elucidates dicarboxylic-acid-specific catabolism in β-proteobacteria for improved plastic monomer upcycling

Dicarboxylic acids are key components of many polymers and plastics, making them a target for both engineered microbial degradation and sustainable bioproduction. In this study, we generated a comprehensive data set of functional evidence for the genetic basis of dicarboxylic and fatty acid metabolism using randomly barcoded transposon sequencing (RB-TnSeq). We identified four β-proteobacteria that displayed robust growth with dicarboxylic acid sole carbon source and cultured their mutant libraries with dicarboxylic and fatty acids with carbon chain lengths from C3 to C12. The resulting fitness data suggested that dicarboxylic and fatty acid metabolisms are largely distinct, and different sets of β-oxidation genes are required for catabolizing dicarboxylic versus fatty acids of the same carbon chain lengths. In addition, we identified transcriptional regulators and transporters with strong fitness phenotypes related to dicarboxylic acid utilization. In Ralstonia sp. UNC404CL21Col (R. CL21), we deleted two transcriptional repressors to improve its utilization of short-chain dicarboxylic acids. We exploited the diacid-utilizing catabolism of R. CL21 to upcycle a mock mixture of the dicarboxylic acids produced when polyethylene is oxidized. After introducing a heterologous indigoidine production pathway, this engineered Ralstonia produced 0.56 ± 0.02 g/L indigoidine from a mixture of dicarboxylic acids as a carbon source, demonstrating the potential of R. CL21 to upcycle plastic wastes to products derived from tricarboxylic acid (TCA) cycle intermediates. IMPORTANCE: Upcycling the carbon in plastic wastes to value-added products is a promising approach to address the plastic waste and climate crises, and dicarboxylic acid metabolism is an important facet of several approaches. Improving our understanding of the genetic basis of this metabolism has the potential to uncover new enzymes and genetic parts for engineered pathways involving dicarboxylic acids. Our data set is the most comprehensive interrogation of dicarboxylic acid catabolism to date, and this work will be of utility to researchers interested in both plastics bioproduction and upcycling applications.

Pearson, Allison N↗
DOE OSTI2025

Viral delivery of recombinases activates heritable genetic switches in plants

Viral vectors provide an increasingly versatile platform for transformation-free reagent delivery to plants. RNA viral vectors can be used to induce gene silencing, overexpress proteins, or introduce gene editing reagents; however, they are often constrained by carrying capacity or restricted tropism in germline cells. Site-specific recombinases that catalyze precise genetic rearrangements are powerful tools for genome engineering that vary in size and, potentially, efficacy in plants. In this work, we show that viral vectors based on tobacco rattle virus (TRV) deliver and stably express four recombinases ranging in size from ~0.6kb to ~1.5kb and achieve simultaneous marker removal and reporter activation through targeted excision in transgenic Nicotiana benthamiana lines. TRV vectors with Cre, FLP, CinH, and Integrase13 efficiently mediated recombination in infected somatic tissue and led to heritable modifications at high frequency. Here, an excision-activated Ruby reporter enabled simple and high-resolution tracing of infected cell lineages without the need for molecular genotyping. Together, our experiments broaden the scope of viral recombinase delivery and offer insights into infection dynamics that may be useful in developing future viral vectors.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Resilient Crop Production for the Bioeconomy: Frontier Science for the Bioeconomy Workshop Series

A bioeconomy based on energy, chemicals, and bioproducts derived from nonfood crops promotes U.S. prosperity, energy independence, and national security. Crop productivity (i.e., yield) affects profitability for farmers, whereas biomass and seed oil quality affects profitability for biorefineries through the conversion efficiency of feedstock crops into energy, chemicals, and bioproducts. Scientific breakthroughs in plant genetics and genomics, ecological processes, bioprocessing, microbial engineering and design, and conversion technologies have improved the potential market viability of products derived from nonfood crops specifically cultivated as biomass and seed oil feedstocks. Improving understanding of a plant’s complex responses to withstand or recover from stress is crucial to maintaining feedstock yield and quality, particularly in challenging production zones. Stress may be related to biotic or abiotic (i.e., nonliving) environmental conditions that negatively affect plant growth, development, and productivity. Research and development to enhance the environmental resilience of feedstock crops will enable improved production by minimizing losses during stress and improving production on currently economically nonviable marginal lands.

09 BIOMASS FUELS↗
NASA NTRS1981

Remote Raman measurement techniques

The use of laser Raman measurement techniques in remote sensing applications is surveyed. A feasibility index is defined as a means to characterize the practicality of a given remote Raman measurement application. Specific applications of Raman scattering to the measurement of atmospheric water vapor profiles, methane plumes from liquid natural gas spills, and subsurface ocean temperature profiles are described. This paper will survey the use of laser Raman measurement techniques in remote sensing applications using as examples specific systems that the Computer Genetics Corporation (CGC) group has developed and engineered.

Leonard, D. A.↗
NASA NTRS1999

Real Time Optima Tracking Using Harvesting Models of the Genetic Algorithm

Tracking optima in real time propulsion control, particularly for non-stationary optimization problems is a challenging task. Several approaches have been put forward for such a study including the numerical method called the genetic algorithm. In brief, this approach is built upon Darwinian-style competition between numerical alternatives displayed in the form of binary strings, or by analogy to 'pseudogenes'. Breeding of improved solution is an often cited parallel to natural selection in.evolutionary or soft computing. In this report we present our results of applying a novel model of a genetic algorithm for tracking optima in propulsion engineering and in real time control. We specialize the algorithm to mission profiling and planning optimizations, both to select reduced propulsion needs through trajectory planning and to explore time or fuel conservation strategies.

Baskaran, Subbiah↗