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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 433 records · Page 24
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Engineered Yeast to Test Risks for Human Exploration of the Lunar Surface

Jessica W. Chau, Natalie N. Ball, Aditya Hindupur, Sandra T. Vu, Jennifer Gil Acevedo, Lauren C. Liddell, Chinmayee Govinda Raj, Gentry, Sergio R. Santa Maria, A. Mark Settles Crewed exploration of the Moon carries risks of long duration exposure to reduced gravity and to deep space radiation. The Lunar Explorer Instrument for space biology Applications (LEIA) investigates the effects of increased radiation and reduced gravity on yeast viability and growth in a Commercial Lunar Payload Services (CLPS) surface mission to the south polar region. LEIA conducts yeast genetics experiments to quantify growth, metabolism, and synthetic biology-enabled production of human nutrients, while taking real time measurements of biologically relevant radiation exposure on the lunar surface. We have engineered beta-carotene producing yeast strains to test the importance of selected DNA damage repair and reactive oxygen species (ROS) defense pathways in mitigating cellular damage from lunar surface radiation. Carotenoids are important dietary antioxidants, and beta-carotene is pro-vitamin A, which is needed for vision and immune function. Carotenoids are sensitive to ROS produced by ionizing radiation and NASA is testing on-demand production of carotenoids from yeast in the BioNutrients space flight experiments. In LEIA, we test the effects of deep space on carotenoid yield in engineered yeast strains. The LEIA team uses CRISPR-Cas9 to engineer yeast to express carotenoids as well as to generate loss-of-function mutations. We are generating mutations in the RAD51 DNA damage repair locus and three genes that function to reduce oxidative damage to the cell: SOD1, SOD2, and TSA1. These strains are tested for carotenoid production using microfluidics and LED spectroscopy to allow remote sensing of cellular growth and carotenoid levels. Keywords: synthetic biology, oxidative stress tolerance, biosensors, space radiation, beyond low Earth orbit, lunar surface, CRISPR/Cas9, gene editing, desiccation, carotenoids.

synthetic biology↗
DOE OSTI2025

Inducible flippase-mediated metabolic engineering of Rhodosporidium toruloides for enhanced 3-hydroxypropionic acid production from corn stover hydrolysate

Rhodosporidium toruloides has gained increasing interests as a promising non-model host organism to produce a wide range of bioproducts from lignocellulosic biomass. Increasing the bioproduct titers, rates, and yields remains a challenge, largely due to a lack of robust and well-characterized genetic tools in this host. Here we developed an inducible flippase (FLP) and flippase recognition target (FRT) system that enables genetic manipulations without the need for additional selection markers. Synthetic inducible promoters were established, enabling regulation of FLP expression and efficient antibiotic marker removal. Leveraging this system, we engineered a strain to optimize 3-hydroxypropionic acid (3HP) production. Over four rounds of iterative genomic editing to resolve pathway bottlenecks, we achieved a 3HP titer of 69.4 g/L in fed-batch fermentation - the highest level reported in yeast from lignocellulosic hydrolysates. The engineered high 3HP producing strain offers a robust platform for sustainable bio-based chemical production from lignocellulosic feedstocks.

3-hydroxypropionic acid↗
DOE OSTI2025

Multigene engineering in plants: Technologies, applications, and future prospects

The emerging bioeconomy presents a promising solution to both economic and environmental challenges. Within the bioeconomy, plants serve as a renewable, sustainable, and cost-effective source of foods, fuels, chemicals, and materials. However, traditional breeding and single-gene engineering approaches fall short in addressing complex traits (e.g., drought tolerance, disease resistance, yield, nutrient use efficiency) which are controlled by multiple genes. The complexity of plant biology often necessitates the use of multigene engineering (MGE), which involves simultaneous ectopic expression, up/down-regulation, or editing of multiple genes, to enhance plant traits relevant to the bioeconomy. These genes may be associated with distinct traits or function as components of specific metabolic and regulatory pathways. This review summarizes current technologies for MGE within the synthetic biology-driven Design-Build-Test-Learn (DBTL) framework, detailing its four key stages: Design – gene construct development; Build – DNA assembly and plant transformation; Test – the molecular, biochemical, and physiological characterization of engineered plants; and Learn – computational modeling to refine, multiplex and iterate the process. Despite good progress in the applications of MGE in biofortification, metabolic engineering, and stress resilience, challenges remain in construct stability, coordinated gene expression, and regulatory predictability. We identified optimization paths and future directions to accelerate MGE deployment in sustainable agriculture, with possible societal benefits including reduced production costs, increased yield, and improved food and nutritional security.

AI-aided plant engineering↗
DOE OSTI2025

Zymomonas mobilis : bringing an ancient human tool into the genomic era

Zymomonas mobilis is an ethanologenic bacterium that has been used for over 1500 years to produce alcoholic beverages. Recently, this microbe has become a top candidate for biofuel production due to its efficient metabolism. Z. mobilis is being developed to utilize lignocellulosic biomass as a feedstock and synthesize a range of valuable chemicals and fuels. Genetic and metabolic engineering strategies are crucial to reach these goals. Recent advances include genome engineering, CRISPR editing, and CRISPRi knockdown of genes. Metabolic engineering has enabled redirection of carbon from the natural product ethanol to chemicals such as 2,3-butanediol and polyhydroxybutyrate. Finally, the approaches summarized here will streamline the development of Z. mobilis as an industrial chassis for sustainable liquid fuels and chemicals.

Boismier, Emma C. [Michigan State Univ., East Lans↗
DOE OSTI2025

From bench to biofactory: high-throughput technologies and automated workflows to accelerate biomanufacturing

Microbial production of target molecules has advanced significantly in recent years driven by innovations in enzyme engineering, DNA synthesis, and genomic editing. However, to access the massive potential of microbial production, a vast parametric space remains to be investigated to optimize these biobased processes for a robust bioeconomy. Here, we review the current state of the art, some key challenges and possible solutions. We see a critical role of automation, high-throughput technologies, self-driving and cloud labs, and data management to enable Artificial Intelligence/Machine Learning and mechanistic models to overcome the design space challenges and accelerate the development of novel bio-based solutions. Accurate models will expedite the development and scale-up of engineered microbes for a range of final products from many starting materials.

Petzold, Christopher J↗
DOE OSTI2024

Technoeconomic analysis of perovskite/silicon tandem solar modules

Tandem photovoltaic (PV) modules offer an opportunity to improve the efficiency and energy yield of available solar resources compared with single-junction devices. Here, we present a cost model and sensitivity analysis of perovskite/silicon (Si) tandem modules to understand how design choices impact overall module costs. We find a minimum sustainable price (MSP) of $\$$0.428/W DC for our baseline two-terminal design and $\$$0.423/W DC for our baseline four-terminal design, each at a module efficiency of 25% and module production of 3 GW per year in the United States. We find that the choice of Si cell architecture, overall module efficiency, and factory throughput have the most significant impacts on cost and competitiveness. The dynamic model provided is designed for researchers, companies, and interested individuals to use and edit as needed to better understand the trade-offs among PV module technologies and enable targeted research to improve module design and fabrication.

14 SOLAR ENERGY↗
DOE OSTI2025

Prediction of neutron production and energy spectrum by the inverse kinematic reaction between an incident 7 Li 3+ beam and a proton target in PHITS

A neutron source using the inverse kinematic reaction between lithium and proton, p( 7 Li, n) 7 Be, achieves forward-directed neutrons, potentially enhancing neutron yield in the forward direction. Despite the advantage, no evaluated-cross-section data for this reaction can be used in Monte Carlo simulation codes, such as PHITS. To solve this problem, this study aims to evaluate the applicability of the user-defined cross-section data, Frag data, for p ( 7 Li, n) 7 Be in PHITS. The simulations reproduced collisions between 7 Li 3+ ions and polypropylene targets. The Frag data was edited based on the JENDL-5 by utilizing the two-body collision kinematics. The neutron yield and angular distribution were investigated in the simulation. As a result, the forward neutron convergence with a reasonable neutron yield and energy spectrum was observed. The expected neutron yield in the forward 1-steradian area is 2.46 × 10 10 n/s when lithium-ion energy and current are 16.45 MeV and 0.1 mA.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

EnergyPlus-MCP: A model-context-protocol server for ai-driven building energy modeling

Traditional building energy modeling with the EnergyPlus building performance simulation engine requires domain expertise, programming skills, and intensive manual efforts limiting its effective adoption. This paper introduces EnergyPlus-MCP, the first open-source Model Context Protocol (MCP) server specifically designed for EnergyPlus simulation workflows, establishing a new foundational infrastructure for AI-driven building energy modeling. The MCP server implements a layered architecture with 35 specialized tools spanning model management, editing and analysis, HVAC and other systems configuration inspection, and simulation execution, enabling Large Language Models to interact with EnergyPlus through conversational interfaces. The server addresses critical workflow barriers by automating model validation, streamlining energy efficiency measures modification, and providing intelligent output management with interactive visualization. Through practical demonstrations using a multi-zone building retrofit analysis, we show how the EnergyPlus-MCP server significantly reduces manual efforts while maintaining full simulation rigor. By providing accessible natural language interfaces to sophisticated building energy analysis, this approach enables scalable deployment of simulation expertise across public and private organizations, educational institutions, and research teams, fundamentally transforming traditional building energy modeling practices.

AI↗
DOE OSTI2024

Small Cells with Big Photosynthetic Productivities: Biotechnological Potential of the Picochlorum Genus

The Picochlorum genus is a distinctive eukaryotic green-algal clade that is the focus of several current biotechnological studies. It is capable of extremely rapid growth rates and has exceptional tolerances to high salinity, intense light, and elevated temperatures. Importantly, it has robust stability and high-biomass productivities in outdoor field trials in seawater. These features have propelled Picochlorum into the spotlight as a promising model for both fundamental and biotechnological research. Recently, several genetic tools, including genome editing, were developed for these algae, enabling insights into Picochlorum photophysiology and algal transformations for expanded capabilities. Here, we survey the Picochlorum genus, its genetic toolbox, recently characterized transformants, and discuss the commercial potential of Picochlorum as a salt-water photoautotrophic biocatalyst.

09 BIOMASS FUELS↗
DOE OSTI2024

Producing multiple chemicals through biological upcycling of waste poly(ethylene terephthalate)

Poly(ethylene terephthalate) (PET) waste is of low degradability in nature, and its mismanagement threatens numerous ecosystems. To combat the accumulation of waste PET in the biosphere, PET bio-upcycling, which integrates chemical pretreatment to produce PET-derived monomers with their microbial conversion into value-added products, has shown promise. The recently discovered Rhodococcus jostii strain PET (RPET) can metabolically degrade terephthalic acid (TPA) and ethylene glycol (EG) as sole carbon sources, and it has been developed into a microbial chassis for PET upcycling. However, the scarcity of synthetic biology tools, specifically designed for the non-model microbe RPET, limits the development of a microbial cell factory for expanding the repertoire of bioproducts from post-consumer PET. Herein, we describe the development of potent genetic tools for RPET, including (1) two inducible and titratable expression systems for tunable gene expression and (2) Serine Integrase-based Recombinational Tools (SIRT) for genome editing. Using these tools, we systematically engineer the RPET strain to ultimately establish microbial supply chains for producing multiple chemicals, including lycopene, lipids, and succinate, from post-consumer PET waste bottles, achieving the highest titer of lycopene ever reported thus far in RPET (i.e., 22.6 mg/L of lycopene, approximately 10,000-fold higher than that of the wild-type strain). Furthermore, this work highlights the great potential of plastic upcycling as a generalizable means of sustainable production of diverse chemicals.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Adaptive laboratory evolution and genetic engineering improved terephthalate utilization in Pseudomonas putida KT2440

Poly(ethylene terephthalate) (PET) is one of the most ubiquitous plastics and can be depolymerized through biological and chemo-catalytic routes to its constituent monomers, terephthalic acid (TPA) and ethylene glycol (EG). TPA and EG can be re-synthesized into PET for closed-loop recycling or microbially converted into higher-value products for open-loop recycling. Here, in this study, we expand on our previous efforts engineering and applying Pseudomonas putida KT2440 for PET conversion by employing adaptive laboratory evolution (ALE) to improve TPA catabolism. Three P. putida strains with varying degrees of metabolic engineering for EG catabolism underwent an automation-enabled ALE campaign on TPA, a TPA and EG mixture, and glucose as a control. ALE increased the growth rate on TPA and TPA-EG mixtures by 4.1- and 3.5-fold, respectively, in approximately 350 generations. Evolved isolates were collected at the midpoints and endpoints of 39 independent ALE experiments, and growth rates were increased by 0.15 and 0.20 h -1 on TPA and a TPA-EG, respectively, in the best performing isolates. Whole-genome re-sequencing identified multiple converged mutations, including loss-of-function mutations to global regulators gacS, gacA, and turA along with large duplication and intergenic deletion events that impacted the heterologously-expressed tphAB II catabolic genes. Reverse engineering of these targets confirmed causality, and a strain with all three regulators deleted and second copies of tphAB II and tpaK displayed improved TPA utilization compared to the base strain. Taken together, an iterative strain engineering process involving heterologous pathway engineering, ALE, whole genome sequencing, and genome editing identified five genetic interventions that improve P. putida growth on TPA, aimed at developing enhanced whole-cell biocatalysts for PET upcycling.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Development, optimization, and application of an episomal plasmid system for Rhodotorula toruloides

Rhodotorula toruloides is an emerging oleaginous yeast with strong potential as a microbial cell factory for the production of acetyl-CoA-derived bioproducts. However, engineering of this organism has been limited by the absence of a functional episomal plasmid system, a foundational genetic tool for rapid gene expression, pathway testing, and CRISPR-based genome engineering. Here, we report the first episomal plasmid system for R. toruloides . Through systematic screening of candidate autonomously replicating sequences (ARSs) from diverse sources, we identified multiple functional ARS elements and selected C63F4, a fragment derived from Contig 63 of R. toruloides CBS14, because of its stable performance. The resulting pC63F4 plasmid was maintained episomally, supported GFP reporter expression, exhibited a copy number of 2.39 ± 0.13, and showed good stability during long term cultivation. To overcome poor transformation efficiency, we developed a Cre- loxP -mediated in vivo re-circularization strategy that enabled reliable delivery of the episomal plasmid. Using this improved system, we demonstrated functional episomal expression of metabolic engineering genes and multi-gene pathways for the production of triacetic acid lactone, fatty alcohols, and limonene. Finally, we leveraged this platform to establish a redesigned CRISPR system that enables seamless genome editing in R. toruloides for the first time, while also simplifying marker recycling. Together, this work establishes a long-needed episomal plasmid platform and associated CRISPR toolkit that will accelerate metabolic engineering, synthetic biology, and fundamental studies in R. toruloides .

CRISPR-Cas9↗
DOE OSTI2025

Improving the Transformation Efficiency of Synechococcus sp. PCC 7002 via Methylome-Guided Premethylation of DNA

Cyanobacteria are promising microbial platforms for a diverse set of biotechnology applications, from living materials to photosynthetic chemical production, but are less well characterized than commonly engineered microbes such as Escherichia coli. This study facilitates genetic engineering in Synechococcus sp. PCC 7002, a fast-growing, halotolerant, and naturally competent strain, by identifying ten native methylation motifs and designing shuttle strains that mimic the native methylation state by expressing a subset of heterologous methyltransferases. DNA methylation in E. coli with as few as two active methyltransferases increased transformation efficiency up to 30-fold across four distinct integration sites in PCC 7002. This work provides an experimental framework to bypass native restriction-modification systems for efficient genome editing and metabolic engineering in nonmodel bacteria.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A Fast-Pass, Desorption Electrospray Ionization Mass Spectrometry Strategy for Untargeted Metabolic Phenotyping

Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) provides direct analytical readouts of small molecules that can be used to characterize the metabolic phenotypes of genetically engineered bacteria. In an effort to accelerate the time frame associated with the screening of mutant libraries, we have developed a high-throughput DESI-MSI analytical workflow implementing a single raster line-scan strategy that facilitates the collection of location-resolved molecular information from engineered strains on a subminute time scale. Evaluation of this “Fast-Pass” DESI-MSI phenotyping workflow on analytical standards demonstrated the capability of acquiring full metabolic profiling information with a throughput of ~40 s per sample. This Fast-Pass strategy was implemented in the analysis of genetically edited Escherichia coli strains that have been engineered to produce various free-fatty acids (FFAs) for applications relevant to biofuels. Due to the untargeted nature of DESI-MSI, the investigation of these strains yielded molecular information for both global metabolites and targeted detection of accumulated bioproducts, allowing simultaneous readouts of strain-specific chemical profiles and comparative measurements of FFA production levels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Transcription factor binding divergence drives transcriptional and phenotypic variation in maize

Regulatory elements are essential components of plant genomes that have shaped the domestication and improvement of modern crops. However, their identity, function and diversity remain poorly characterized, limiting our ability to harness their full power for agricultural advances using induced or natural variation. Here, in this study, we mapped transcription factor (TF) binding for 200 TFs from 30 families in two distinct maize inbred lines historically used in maize breeding. TF binding comparison revealed widespread differences between inbreds, driven largely by structural variation, that correlated with gene expression changes and explained complex quantitative trait loci such as Vgt1, an important determinant of flowering time, and DICE, an herbivore resistance enhancer. CRISPR–Cas9 editing of TF binding regions validated the function and structure of regulatory regions at various loci controlling plant architecture and biotic resistance. Our maize TF binding catalogue identifies functional regulatory regions and enables collective and comparative analysis, highlighting its value for agricultural improvement.

Galli, Mary [Rutgers Univ., Piscataway, NJ (United↗
DOE OSTI2025

Addressing genome scale design tradeoffs in Pseudomonas putida for bioconversion of an aromatic carbon source

Genome-scale metabolic models (GSMM) are commonly used to identify gene deletion sets that result in growth coupling and pairing product formation with substrate utilization and can improve strain performance beyond levels typically accessible using traditional strain engineering approaches. However, sustainable feedstocks pose a challenge due to incomplete high-resolution metabolic data for non-canonical carbon sources required to curate GSMM and identify implementable designs. Here we address a four-gene deletion design in the Pseudomonas putida KT2440 strain for the lignin-derived non-sugar carbon source, p-coumarate (p-CA), that proved challenging to implement. We examine the performance of the fully implemented design for p-coumarate to glutamine, a useful biomanufacturing intermediate. In this study glutamine is then converted to indigoidine, an alternative sustainable pigment and a model heterologous product that is commonly used to colorimetrically quantify glutamine concentration. Through proteomics, promoter-variation, and growth characterization of a fully implemented gene deletion design, we provide evidence that aromatic catabolism in the completed design is rate-limited by fumarase hydratase (FUM) enzyme activity in the citrate cycle and requires careful optimization of another fumarate hydratase protein (PP_0897) expression to achieve growth and production. A double sensitivity analysis also confirmed a strict requirement for fumarate hydratase activity in the strain where all genes in the growth coupling design have been implemented. Metabolic cross-feeding experiments were used to examine the impact of complete removal of the fumarase hydratase reaction and revealed an unanticipated nutrient requirement, suggesting additional functions for this enzyme. While a complete implementation of the design was achieved, this study highlights the challenge of completely inactivating metabolic reactions encoded by under-characterized proteins, especially in the context of multi-gene edits.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Fourier-based three-dimensional multistage transformer for aberration correction in multicellular specimens

High-resolution tissue imaging is often compromised by sample-induced optical aberrations that degrade resolution and contrast. Although wavefront sensor-based adaptive optics (AO) can measure these aberrations, such hardware solutions are typically complex, expensive to implement and slow when serially mapping spatially varying aberrations across large fields of view. Here we introduce AOViFT (adaptive optical vision Fourier transformer)—a machine learning-based aberration sensing framework built around a three-dimensional multistage vision transformer that operates on Fourier domain embeddings. AOViFT infers aberrations and restores diffraction-limited performance in puncta-labeled specimens with substantially reduced computational cost, training time and memory footprint compared to conventional architectures or real-space networks. We validated AOViFT on live gene-edited zebrafish embryos, demonstrating its ability to correct spatially varying aberrations using either a deformable mirror or postacquisition deconvolution. By eliminating the need for the guide star and wavefront sensing hardware and simplifying the experimental workflow, AOViFT lowers technical barriers for high-resolution volumetric microscopy across diverse biological samples.

Alshaabi, Thayer [Howard Hughes Medical Institute,↗