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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Direct genome-scale screening of Gluconobacter oxydans B58 for rare earth element bioleaching

Abstract The transition to a sustainable energy economy will require an enormous increase in the supply of rare earth elements (REEs). Bioleaching offers a promising alternative to conventional hydrometallurgical methods for REE extraction from low-grade ores. However, exploiting this potential remains challenging due to large gaps in our understanding of the genetics involved, and inadequate biological tools to address them. We generated a highly non-redundant whole-genome knockout collection for the bioleaching microbe Gluconobacter oxydans B58, reducing redundancy by 85% compared to the previous best collection. This new collection was directly screened for bioleaching neodymium from a synthetic monazite powder, identifying 89 genes important for bioleaching, 68 of which have not previously been associated with this mechanism. We conducted bench-scale experiments to validate the extraction efficiency of promising strains: 8 demonstrated significant increases in extraction by up to 111% (δ GO_1598 , disruption of the gene encoding the orotate phosphoribosyltransferase enzyme PyrE), and one strain significantly reduced it by 97% (δ GO_1096 , disruption of the gene encoding the GTP-binding protein TypA). Notable changes in pH were only observed for 3 strains, suggesting an important role for non-acid mechanisms in bioleaching. These findings provide valuable insights into further enhancing REE-bioleaching by G. oxydans through genetic engineering.

Marecos, Sabrina (ORCID:0000000158529933)↗
DOE OSTI2026

Metagenomes and metagenome-assembled genomes from a nutrient removal plant at Los Angeles County Sanitation Districts (LACSD) that transitioned from high to low dissolved oxygen

Operating biological nutrient removal (BNR) wastewater treatment plants with low dissolved oxygen (DO) conditions can reduce energy costs. We report on five metagenomes and 492 metagenome-assembled genomes (MAGs) obtained from samples collected at the Pomona water reclamation plant before and after a DO reduction from 3.5 to 0.7 mg/L.

dissolved oxygen↗
DOE OSTI2025

Creation of an Acyltransferase Toolbox for Plant Biomass Engineering (Final Report)

The major goal of this project was to expand our understanding of acyl‐CoA ligases and BAHD acyltransferases and their utility in plant engineering. We combined bioinformatic analysis of genes and transcripts with functional fingerprinting of synthesized genes produced by JGI. Best candidates from this experimental pipeline were transferred into bioenergy plants to study their effects on lignin composition. We found combinations of ligase and transferase genes encoding enzymes with interesting catalytic specificities. Our work demonstrated the feasibility of use of acyl-CoA ligases and BAHD acyltransferases to alter the composition of plant cell walls without deleterious effects on the modified plant.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Methane utilization in Methylomicrobium alcaliphilum 20Z R : a systems approach

Biological methane utilization, one of the main sinks of the greenhouse gas in nature, represents an attractive platform for production of fuels and value-added chemicals. Despite the progress made in our understanding of the individual parts of methane utilization, our knowledge of how the whole-cell metabolic network is organized and coordinated is limited. Attractive growth and methane-conversion rates, a complete and expert-annotated genome sequence, as well as large enzymatic, 13 C-labeling, and transcriptomic datasets make Methylomicrobium alcaliphilum 20Z R an exceptional model system for investigating methane utilization networks. Here we present a comprehensive metabolic framework of methane and methanol utilization in M. alcaliphilum 20Z R . A set of novel metabolic reactions governing carbon distribution across central pathways in methanotrophic bacteria was predicted by in-silico simulations and confirmed by global non-targeted metabolomics and enzymatic evidences. Our data highlight the importance of substitution of ATP-linked steps with PPi-dependent reactions and support the presence of a carbon shunt from acetyl-CoA to the pentose-phosphate pathway and highly branched TCA cycle. The diverged TCA reactions promote balance between anabolic reactions and redox demands. As a result, the computational framework of C 1 -metabolism in methanotrophic bacteria can represent an efficient tool for metabolic engineering or ecosystem modeling.

09 BIOMASS FUELS↗
DOE OSTI2023

Introgression and persistence of cultivar alleles in wild carrot ( Daucus carota ) populations in the United States

Abstract Premise Cultivated species and their wild relatives often hybridize in the wild, and the hybrids can survive and reproduce in some environments. However, it is unclear whether cultivar alleles are permanently incorporated into the wild genomes or whether they are purged by natural selection. This question is key to accurately assessing the risk of escape and spread of cultivar genes into wild populations. Methods We used genomic data and population genomic methods to study hybridization and introgression between cultivated and wild carrot (Daucus carota) in the United States. We used single nucleotide polymorphisms (SNPs) obtained via genotyping by sequencing for 450 wild individuals from 29 wild georeferenced populations in seven states and 144 cultivars from the United States, Europe, and Asia. Results Cultivated and wild carrot formed two genetically differentiated groups, and evidence of crop–wild admixture was detected in several but not all wild carrot populations in the United States. Two regions were identified where cultivar alleles were present in wild carrots: California and Nantucket Island (Massachusetts). Surprisingly, there was no evidence of introgression in some populations with a long‐known history of sympatry with the crop, suggesting that post‐hybridization barriers might prevent introgression in some areas. Conclusions Our results provide support for the introgression and long‐term persistence of cultivar alleles in wild carrots populations. We thus anticipate that the release of genetically engineered (GE) cultivars would lead to the introduction and spread of GE alleles in wild carrot populations.

Plant Sciences↗
DOE OSTI2026

Hyporheic zone, river, and groundwater metagenome resolved genomes and rpS3 genes in East River Watershed, Colorado USA Summer 2020, 2021

Here we present metagenome assembled genomes (MAGs) for the bacterial and archaeal communities from water filter collected across 8 locations along the East River Watershed, CO, and 1 nearby groundwater well. The purpose was to look for connectivity and similarities across the network and to see the impact of the groundwater. As a part of Lawrence Berkeley National Laboratory (LBNL) Watershed Science Focus Area (SFA), we assessed community composition and strain similarities between the sites and we also compared it to previous metagenomic studies within the watershed looking at floodplain (Matheus Carnevali et al. 2021) and hillslope (Lavy et al. 2019) microbiomes. Here we present metagenome assembled genomes (MAGs) for the bacterial and archaeal communities from filters across 8 locations during August 2020 and July 2021. This resulted in 32 samples. The groundwater sample was sequenced at UC Berkley's QB3. The other 31 samples were sequenced at University of Maryland. Metagenomes were assembled using four autobinners and the best bins were selected using dasTool. The genomes were dereplicated at 95% with dRep and the subset of winning genomes were manually curated based on visual inspection of taxonomic profile, GC content, coverage, and a set of 51 bacterial single copy genes (BSCG), and 38 archaeal signal copy genes (ASCG). The dataset includes a zip file of 311 genomes (HZ_River_SW_MAGS_Dereplicated_95.zip). The dataset additionally includes a zipped file of ribosomal protein small subunit 3 (rpS3) proteins from the hyporheic zone and river data (rpS3_Proteins_HZ_River.zip), a metadata file used to register associated samples with IGSNs (International Generic Sample Numbers) (samples.csv), a location metadata file (locations.csv). This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

DNA↗
DOE OSTI2025

Hydrophobins from Aspergillus Mediate Fungal Interactions with Microplastics

Microplastics cause negative environmental consequences such as the release of toxic additive leachates, increased greenhouse gas emissions during degradation, and threaten food chains . Microplastic particles are known to serve as a vector for transport of microbes (fungi and bacteria) to new environments, threatening biodiversity. Robust biofilm formation makes fungi a candidate to collect and remediate environmental microplastics. However, fungal-microplastic colonization mechanisms have yet to be explored. In this work, we aim to understand which fungal molecules mediate microplastics binding. We examine common fungal genus Aspergillus , which we found binds microplastics tightly, removing particles from suspension. Upon inoculation of Aspergilli with microplastics particles, up to 3.85 ± 1.48 g of microplastics were flocculated per gram of dry fungal biomass; this phenomenon was observed across various plastics ranging in size from 0.05 to 5 mm. Gene knockouts revealed that hydrophobins drive microplastic-fungi binding, evidenced by a decrease in flocculation relative to wild-type Aspergillus fumigatus. Moreover, purified hydrophobins flocculated microplastics independently of the fungus, validating their ability to bind to microplastics. Furthermore, our work elucidates a role for hydrophobins in fungal colonization of microplastics and highlights a target for mitigating the harm of microplastics through engineered fungal-microplastic interactions.

biofilms↗
DOE OSTI2017

Programming mRNA decay to modulate synthetic circuit resource allocation

Synthetic circuits embedded in host cells compete with cellular processes for limited intracellular resources. Here we show how funnelling of cellular resources, after global transcriptome degradation by the sequence-dependent endoribonuclease MazF, to a synthetic circuit can increase production. Target genes are protected from MazF activity by recoding the gene sequence to eliminate recognition sites, while preserving the amino acid sequence. The expression of a protected fluorescent reporter and flux of a high-value metabolite are significantly enhanced using this genome-scale control strategy. Proteomics measurements discover a host factor in need of protection to improve resource redistribution activity. A computational model demonstrates that the MazF mRNA-decay feedback loop enables proportional control of MazF in an optimal operating regime. Transcriptional profiling of MazF-induced cells elucidates the dynamic shifts in transcript abundance and discovers regulatory design elements. Altogether, our results suggest that manipulation of cellular resource allocation is a key control parameter for synthetic circuit design.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Integration of genome-scale metabolic model with biorefinery process model reveals market-competitive carbon-negative sustainable aviation fuel utilizing microbial cell mass lipids and biogenic CO 2

Producing scalable, economically viable, low-carbon biofuels or biochemicals hinges on more efficient bioconversion processes. While microbial conversion can offer robust solutions, the native microbial growth process often redirects a large fraction of carbon to CO 2 and cell mass. By integrating genome-scale metabolic models with techno-economic and life cycle assessment models, this study analyzes the effects of converting cell mass lipids to hydrocarbon fuels, and CO 2 to methanol on the facility’s costs and life-cycle carbon footprint. Results show that upgrading microbial lipids or both microbial lipids and CO 2 using renewable hydrogen produces carbon-negative bisabolene. Additionally, on-site electrolytic hydrogen production offers a supply of pure oxygen to use in place of air for bioconversion and fuel combustion in the boiler. To reach cost parity with conventional jet fuel, renewable hydrogen needs to be produced at less than $\$2.2$ to $\$3.1$/kg, with a bisabolene yield of 80% of the theoretical yield, along with cell mass and CO 2 yields of 22 wt% and 54 wt%, respectively. The economic combination of cell mass, CO 2 , and bisabolene yields demonstrated in this study provides practical insights for prioritizing research, selecting suitable hosts, and determining necessary engineered production levels.

09 BIOMASS FUELS↗
DOE OSTI2021

Co-expression of a β-d-xylosidase from Thermotoga maritima and a Family 10 xylanase from A. cellulolyticus significantly improves the xylan degrading activity of the Caldicellulosiruptor bescii exoproteome

Caldicellulosiruptor species are hyperthermophilic, Gram-positive, anaerobes and the most thermophilic cellulolytic bacteria so far described. They have been engineered to convert switchgrass to ethanol without pretreatment and represent a promising platform for the production of fuels, chemicals and materials from plant biomass. Xylooligomers such as xylobiose and xylotriose that result from the breakdown of plant biomass more strongly inhibit cellulase activity than do glucose or cellobiose. High concentrations of xylobiose and xylotriose, are present in C. bescii fermentations after 90 h incubation and removal or breakdown of these types of xylooligomers is crucial to achieve high conversion of plant biomass to product. In previous studies the addition of exogenous β-d-xylosidase substantially improved the performance of glucanases and xylanases in vitro. β-d-Xylosidases are, in fact, essential enzymes in commercial preparations for efficient deconstruction of plant biomass. In addition, the combination of xylanase and β-d-xylosidase is known to exhibit synergistic action on xylan degradation. In spite of its ability to grow efficiently on xylan substrates, no extracellular β-d-xylosidase was identified in the C. bescii genome. Here we report that the co-expression of a thermal stable β-d-xylosidase from Thermotoga maritima and a xylanase from Acidothermus cellulolyticus in a C. bescii strain containing the A. cellulolyticus E1 endoglucanase significantly increased the activity of the exoproteome as well as growth on xylan substrates. The combination of these enzymes also resulted in increased growth on crystalline cellulose in the presence of exogeneous xylan.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Metal Hydride Material Development for High Efficiency and Low Cost Hydrogen Compressors

To make the hydrogen economy realistic at a large scale, one of the main technical issues to be overcome is relative to the high-pressure hydrogen delivery. Traditional hydrogen compressors suffer from high operating and maintenance costs and high capital investment. Metal hydride based compressors represent a realistic alternative that can potentially overcome all of the technical hurdles of the traditional mechanical systems. However, to date, the metal hydrides, available for this type of application (e.g. rare earth based materials), are generally based on expensive compounds and elements. A novel materials-genome based high throughput technique was established to define and develop a new class of materials for hydrogen compression. Specific material properties, required to meet the techno-economic targets for hydrogen compression systems, were identified. After validation of the high throughput methodology by comparing the results with the available material data, the technique was applied to identify preliminary new material formulations that meet the targets. A novel techno-economic analysis constrained machine learning system was developed and applied to identify the new set of metal hydride materials.

08 HYDROGEN↗
DOE OSTI2016

Workshop Report: Systems Biology for Organotypic Cell Cultures

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, “organotypic” cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomic data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data.

3D models↗
DOE OSTI2016

Systems Biology for Organotypic Cell Cultures

Translating in vitro biological data into actionable information related to human health holds the potential to improve disease treatment and risk assessment of chemical exposures. While genomics has identified regulatory pathways at the cellular level, translation to the organism level requires a multiscale approach accounting for intra-cellular regulation, inter-cellular interaction, and tissue/organ-level effects. Tissue-level effects can now be probed in vitro thanks to recently developed systems of three-dimensional (3D), multicellular, “organotypic” cell cultures, which mimic functional responses of living tissue. However, there remains a knowledge gap regarding interactions across different biological scales, complicating accurate prediction of health outcomes from molecular/genomic data and tissue responses. Systems biology aims at mathematical modeling of complex, non-linear biological systems. We propose to apply a systems biology approach to achieve a computational representation of tissue-level physiological responses by integrating empirical data derived from organotypic culture systems with computational models of intracellular pathways to better predict human responses. Successful implementation of this integrated approach will provide a powerful tool for faster, more accurate and cost-effective screening of potential toxicants and therapeutics. On September 11, 2015, an interdisciplinary group of scientists, engineers, and clinicians gathered for a workshop in Research Triangle Park, North Carolina, to discuss this ambitious goal. Participants represented laboratory-based and computational modeling approaches to pharmacology and toxicology, as well as the pharmaceutical industry, government, non-profits, and academia. Discussions focused on identifying critical system perturbations to model, the computational tools required, and the experimental approaches best suited to generating key data. This consensus report summarizes the discussions held.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Gene network centrality analysis identifies key regulators coordinating day-night metabolic transitions in Synechococcus elongatus PCC 7942 despite limited accuracy in predicting direct regulator-gene interactions

Synechococcus elongatus PCC 7942 is a model organism for studying circadian regulation and bioproduction, where precise temporal control of metabolism significantly impacts photosynthetic efficiency and CO 2 -to-bioproduct conversion. Despite extensive research on core clock components, our understanding of the broader regulatory network orchestrating genome-wide metabolic transitions remains incomplete. We address this gap by applying machine learning tools and network analysis to investigate the transcriptional architecture governing circadian-controlled gene expression. While our approach showed moderate accuracy in predicting individual transcription factor-gene interactions - a common challenge with real expression data - network-level topological analysis successfully revealed the organizational principles of circadian regulation. Our analysis identified distinct regulatory modules coordinating day-night metabolic transitions, with photosynthesis and carbon/nitrogen metabolism controlled by day-phase regulators, while nighttime modules orchestrate glycogen mobilization and redox metabolism. Through network centrality analysis, we identified potentially significant but previously understudied transcriptional regulators: HimA as a putative DNA architecture regulator, and TetR and SrrB as potential coordinators of nighttime metabolism, working alongside established global regulators RpaA and RpaB. This work demonstrates how network-level analysis can extract biologically meaningful insights despite limitations in predicting direct regulatory interactions. The regulatory principles uncovered here advance our understanding of how cyanobacteria coordinate complex metabolic transitions and may inform metabolic engineering strategies for enhanced photosynthetic bioproduction from CO 2 .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Molecular Characterization of Bacterial Respiration on Minerals

The overall aim of this project was to contribute to our fundamental understanding of proteins and biological processes under extreme environmental conditions. We sought to define the biochemical and physiological mechanisms that underlie biodegradative and other cellular processes in normal, extreme, and engineered environments. Toward that end, we sought to understand the substrate oxidation pathways, the electron transport mechanisms, and the modes of energy conservation employed during respiration by bacteria on soluble iron and insoluble sulfide minerals. In accordance with these general aims, the specific aims were two-fold: To identify, separate, and characterize the extracellular biomolecules necessary for aerobic respiration on iron under strongly acidic conditions; and to elucidate the molecular principles whereby these bacteria recognize and adhere to their insoluble mineral substrates under harsh environmental conditions. The results of these studies were described in a total of nineteen manuscripts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Designing Metabolic Division of Labor in Microbial Communities

ABSTRACT Microbes face a trade-off between being metabolically independent and relying on neighboring organisms for the supply of some essential metabolites. This balance of conflicting strategies affects microbial community structure and dynamics, with important implications for microbiome research and synthetic ecology. A “gedanken” (thought) experiment to investigate this trade-off would involve monitoring the rise of mutual dependence as the number of metabolic reactions allowed in an organism is increasingly constrained. The expectation is that below a certain number of reactions, no individual organism would be able to grow in isolation and cross-feeding partnerships and division of labor would emerge. We implemented this idealized experiment using in silico genome-scale models. In particular, we used mixed-integer linear programming to identify trade-off solutions in communities of Escherichia coli strains. The strategies that we found revealed a large space of opportunities in nuanced and nonintuitive metabolic division of labor, including, for example, splitting the tricarboxylic acid (TCA) cycle into two separate halves. The systematic computation of possible solutions in division of labor for 1-, 2-, and 3-strain consortia resulted in a rich and complex landscape. This landscape displayed a nonlinear boundary, indicating that the loss of an intracellular reaction was not necessarily compensated for by a single imported metabolite. Different regions in this landscape were associated with specific solutions and patterns of exchanged metabolites. Our approach also predicts the existence of regions in this landscape where independent bacteria are viable but are outcompeted by cross-feeding pairs, providing a possible incentive for the rise of division of labor. IMPORTANCE Understanding how microbes assemble into communities is a fundamental open issue in biology, relevant to human health, metabolic engineering, and environmental sustainability. A possible mechanism for interactions of microbes is through cross-feeding, i.e., the exchange of small molecules. These metabolic exchanges may allow different microbes to specialize in distinct tasks and evolve division of labor. To systematically explore the space of possible strategies for division of labor, we applied advanced optimization algorithms to computational models of cellular metabolism. Specifically, we searched for communities able to survive under constraints (such as a limited number of reactions) that would not be sustainable by individual species. We found that predicted consortia partition metabolic pathways in ways that would be difficult to identify manually, possibly providing a competitive advantage over individual organisms. In addition to helping understand diversity in natural microbial communities, our approach could assist in the design of synthetic consortia.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Metabolic Model of the Nitrogen-Fixing Obligate Aerobe Azotobacter vinelandii Predicts Its Adaptation to Oxygen Concentration and Metal Availability

There is considerable interest in promoting biological nitrogen fixation (BNF) as a mechanism to reduce the inputs of nitrogenous fertilizers in agriculture, but considerable fundamental knowledge gaps still need to be addressed. BNF is catalyzed by nitrogenase, which requires a large input of energy in the form of ATP and low potential electrons. Diazotrophs that respire aerobically have an advantage in meeting the ATP demands of BNF but face challenges in protecting nitrogenase from inactivation by oxygen. Here, we constructed a genome-scale metabolic model of the nitrogen-fixing bacterium Azotobacter vinelandii, which uses a complex respiratory protection mechanism to consume oxygen at a high rate to keep intracellular conditions microaerobic. Our model accurately predicts growth rate under high oxygen and substrate concentrations, consistent with a large electron flux directed to the respiratory protection mechanism. While a partially decoupled electron transport chain compensates for some of the energy imbalance under high-oxygen conditions, it does not account for all substrate intake, leading to increased maintenance rates. Interestingly, the respiratory protection mechanism is required for accurate predictions even when ammonia is supplemented during growth, suggesting that the respiratory protection mechanism might be a core principle of metabolism and not just used for nitrogenase protection. We have also shown that rearrangement of flux through the electron transport system allows A. vinelandii to adapt to different oxygen concentrations, metal availability, and genetic disruption, which cause an ammonia excretion phenotype. Accurately determining the energy balance in an aerobic nitrogen-fixing metabolic model is required for future engineering approaches.

59 BASIC BIOLOGICAL SCIENCES↗