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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

3,3’-Diindolylmethane Exhibits Significant Metabolism After Oral Dosing in Humans

3,3’-Diindolylmethane (DIM), a major phytochemical derived from ingestion of cruciferous vegetables such as Brussels sprouts, is also a dietary supplement. In preclinical models, DIM is an effective cancer chemopreventive agent and has been studied in a number of clinical trials. Previous pharmacokinetic studies in preclinical and clinical models have not reported DIM metabolites in plasma or urine following oral dosing and the pharmacological actions of DIM on target tissues is assumed to be solely via the parent compound. Seven subjects (6 males and 1 female) ranging from 26-65 years of age, on a cruciferous vegetable-restricted diet prior to and during the study, took 2 BioResponse-DIM® 150 mg capsules (45.3 mg DIM/capsule) in the evening for one week with a final dose the morning of the first blood draw. A complete time course was performed with plasma and urine collected over 48 hours and analyzed by UPLC-MS/MS. In addition to parent DIM, two mono-hydroxylated (2-ox- and 3-methylenehydroxy-DIM) and 1 dihydroxylated (3-methylenehydroxy-2-ox-DIM) metabolites, along with their sulfate and glucuronide conjugates, were present in both plasma and urine. The results reported here are indicative of significant phase 1 and phase 2 metabolism and differ from previous pharmacokinetic studies in rodents and humans which reported only parent DIM present following oral administration.

Vermillion-Maier, Monica↗
DOE OSTI2024

Sulfur assimilation using gaseous carbonyl sulfide by the soil fungus Trichoderma harzianum

Fungi have the capacity to assimilate a diverse range of both inorganic and organic sulfur compounds. It has been recognized that all sulfur sources taken up by fungi are in soluble forms. In this study, we present evidence that fungi can utilize gaseous carbonyl sulfide (COS) for the assimilation of a sulfur compound. We found that the filamentous fungus Trichoderma harzianum strain THIF08, which has constitutively high COS-degrading activity, was able to grow with COS as the sole sulfur source. Cultivation with 34 S-labeled COS revealed that sulfur atom from COS was incorporated into intracellular metabolites such as glutathione and ergothioneine. COS degradation by strain THIF08, in which as much of the moisture derived from the agar medium as possible was removed, indicated that gaseous COS was taken up directly into the cell. Escherichia coli transformed with a COS hydrolase (COSase) gene, which is clade D of the β-class carbonic anhydrase subfamily enzyme with high specificity for COS but low activity for CO 2 hydration, showed that the COSase is involved in COS assimilation. Comparison of sulfur metabolites of strain THIF08 revealed a higher relative abundance of reduced sulfur compounds under the COS-supplemented condition than the sulfate-supplemented condition, suggesting that sulfur assimilation is more energetically efficient with COS than with sulfate because there is no redox change of sulfur. Phylogenetic analysis of the genes encoding COSase, which are distributed in a wide range of fungal taxa, suggests that the common ancestor of Ascomycota, Basidiomycota, and Mucoromycota acquired COSase at about 790–670 Ma.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Bridging the Gap between Analytical and Microbial Sciences in Microbiome Research

Metabolites from the microbiome influence human, animal, and environmental health, but the diversity and functional roles of these compounds have only begun to be elucidated. Comprehensively characterizing these molecules are significant challenges, as it requires expertise in analytical methods, such as mass spectrometry and nuclear magnetic resonance spectroscopy, skills that not many traditional microbiologists or microbial ecologists possess. This creates a gap between microbiome scientists that want to understand the role of microbial metabolites in microbiome systems and the skills required to generate and interpret complex metabolomics data sets. To bridge this gap, microbiome scientists should engage analytical chemists to best understand the underlying chemical principles of the data. Conversely, analytical scientists are encouraged to engage with microbiome scientists to better understand the biological questions being asked with metabolomics and to best communicate its intricacies. Better communication across the chemistry/biology disciplines will further reveal the “dark matter” within microbiomes that maintain healthy humans and environments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Decoding the chemical language of Suillus fungi: genome mining and untargeted metabolomics uncover terpene chemical diversity

ABSTRACT Ectomycorrhizal fungi establish mutually beneficial relationships with trees, trading nutrients for carbon. Suillus are ectomycorrhizal fungi that are critical to the health of boreal and temperate forest ecosystems. Comparative genomics has identified a high number of non-ribosomal peptide synthetase and terpene biosynthetic gene clusters (BGC) potentially involved in fungal competition and communication. However, the functionality of these BGCs is not known. This study employed co-culture techniques to activate BGC expression and then used metabolomics to investigate the diversity of metabolic products produced by three Suillus species ( Suillus hirtellus EM16, Suillus decipiens EM49, and Suillus cothurnatus VC1858), core members of the pine microbiome. After 28 days of growth on solid media, liquid chromatography–tandem mass spectrometry identified a diverse range of extracellular metabolites (exometabolites) along the interaction zone between Suillus co-cultures. Prenol lipids were among the most abundant chemical classes. Out of the 62 unique terpene BGCs predicted by genome mining, 41 putative prenol lipids (includes 37 putative terpenes) were identified across the three Suillus species using metabolomics. Notably, some terpenes were significantly more abundant in co-culture conditions. For example, we identified a metabolite matching to isomers isopimaric acid, sandaracopimaric acid, and abietic acid, which can be found in pine resin and play important roles in host defense mechanisms and Suillus spore germination. This research highlights the importance of combining genomics and metabolomics to advance our understanding of the chemical diversity underpinning fungal signaling and communication. IMPORTANCE Using a combination of genomics and metabolomics, this study’s findings offer new insights into the chemical diversity of Suillus fungi, which serve a critical role in forest ecosystems.

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

Wetlands harbor lactic acid-driven chain elongators

Wetlands are globally significant carbon storage hotspots. Recent research has suggested that microbially derived metabolites may contribute to soil organic matter formation. Identifying pathways driving the formation of such metabolites is critical to understand the global impact of wetland carbon cycling. Here, we evaluate the presence of chain-elongating organisms converting two to three carbon compounds (i.e., lactic and acetic acid) to medium-chain carboxylic acids (MCCA; i.e., six-carbon caproic acid) in wetland soils. We demonstrate the enrichment of a lactic acid-driven chain-elongating community from wetland soils producing a mixture of butyric and caproic acid. The enriched community was dominated by Clostridiaceae, Ruminococcaceae, and Lachnospiraceae, three families with known chain elongators. Amplicon sequencing identified three Ruminococcaceae and one Clostridiaceae zero-radius OTU (zOTU) that were (i) present in the soil, (ii) enriched over 1% relative abundance in the bioreactor, and (iii) were closely related to known chain elongators. Moreover, close relatives of the three Ruminococcaceae zOTU were also observed in several other wetland microbiomes. From this observation, we conclude that close relatives of known chain elongators, potentially capable of lactic acid-driven MCCA production themselves, are present in wetland soils. This observation may have implications for our understanding of carbon cycling and storage in wetland ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Cryptococcus neoformans Secretes Small Molecules That Inhibit IL-1 β Inflammasome-Dependent Secretion

Cryptococcus neoformans is an encapsulated yeast that causes disease mainly in immunosuppressed hosts. It is considered a facultative intracellular pathogen because of its capacity to survive and replicate inside phagocytes, especially macrophages. This ability is heavily dependent on various virulence factors, particularly the glucuronoxylomannan (GXM) component of the polysaccharide capsule. Inflammasome activation in phagocytes is usually protective against fungal infections, including cryptococcosis. Nevertheless, recognition of C. neoformans by inflammasome receptors requires specific changes in morphology or the opsonization of the yeast, impairing proper inflammasome function. In this context, we analyzed the impact of molecules secreted by C. neoformans B3501 strain and its acapsular mutant Δcap67 in inflammasome activation in an in vitro model. Our results showed that conditioned media derived from B3501 was capable of inhibiting inflammasome-dependent events (i.e., IL-1β secretion and LDH release via pyroptosis) more strongly than conditioned media from Δcap67, regardless of GXM presence. We also demonstrated that macrophages treated with conditioned media were less responsive against infection with the virulent strain H99, exhibiting lower rates of phagocytosis, increased fungal burdens, and enhanced vomocytosis. Moreover, we showed that the aromatic metabolite DL-Indole-3-lactic acid (ILA) and DL-p-Hydroxyphenyllactic acid (HPLA) were present in B3501’s conditioned media and that ILA alone or with HPLA is involved in the regulation of inflammasome activation by C. neoformans. These results were confirmed by in vivo experiments, where exposure to conditioned media led to higher fungal burdens in Acanthamoeba castellanii culture as well as in higher fungal loads in the lungs of infected mice. Overall, the results presented show that conditioned media from a wild-type strain can inhibit a vital recognition pathway and subsequent fungicidal functions of macrophages, contributing to fungal survival in vitro and in vivo and suggesting that secretion of aromatic metabolites, such as ILA, during cryptococcal infections fundamentally impacts pathogenesis.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

MetConSIN

Metabolic Context Species Interaction Networks (MetConSIN) generates microbe-metabolte and metabolite-metabolite interaction networks using constraint based metabolic modeling. To do this, MetConSIN simulates with the dynamic FBA system and saves the sequence of interaction networks implied by that system, as well as the time-average network.

Brunner, James↗
DOE OSTI2022

EMSL-Computing/PeakDecoder

PeakDecoder is a machine learning (ML)-based metabolite identification algorithm for multidimensional mass spectrometry measurements incorporating liquid chromatography (LC) and ion mobility spectrometry (IM) separations, and collecting extensive fragmentation spectra with data-independent acquisition (DIA) methods: LC-IM-DIA-MS. The algorithm learns to distinguish true co-elution and co-mobility from raw data and calculates metabolite identification error rates.

Bilbao Pena, Aivett↗
DOE OSTI2024

maranasgroup/yeastsMFA

The parameterization of kinetic models requires measurement of fluxes and/or metabolite levels for a base strain and a few genetic perturbations thereof. Unlike stoichiometric models that are mostly invariant to the specific strain, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. This important question underpins the applicability range and prediction limits of kinetic reconstructions. To this end, herein we parameterize two separate large-scale kinetic models using K-FIT with genome-wide coverage corresponding to two distinct strains of Saccharomyces cerevisiae: CEN.PK 113-7D strain (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by 13C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process.

Dinh, Hoang↗
DOE OSTI2023

maranasgroup/k-sacce306

The parameterization of kinetic models requires measurement of fluxes and/or metabolite levels for a base strain and a few genetic perturbations thereof. Unlike stoichiometric models that are mostly invariant to the specific strain, it remains unclear whether kinetic models constructed for different strains of the same species have similar or significantly different kinetic parameters. This important question underpins the applicability range and prediction limits of kinetic reconstructions. To this end, herein we parameterize two separate large-scale kinetic models using K-FIT with genome-wide coverage corresponding to two distinct strains of Saccharomyces cerevisiae: CEN.PK 113-7D strain (model k-sacce306-CENPK), and growth-deficient BY4741 (isogenic to S288c; model k-sacce306-BY4741). The metabolic network for each model contains 306 reactions, 230 metabolites, and 119 substrate-level regulatory interactions. The two models (for CEN.PK and BY4741) recapitulate, within one standard deviation, 77% and 75% of the fitted dataset fluxes, respectively, determined by 13C metabolic flux analysis for wild-type and eight single-gene knockout mutants of each strain. Strain-specific kinetic parameterization results indicate that key enzymes in the TCA cycle, glycolysis, and arginine and proline metabolism drive the metabolic differences between these two strains of S. cerevisiae. Our results suggest that although kinetic models cannot be readily used across strains as stoichiometric models, they can capture species-specific information through the kinetic parameterization process.

Dinh, Hoang↗
DOE OSTI2021

Altered Cardiac Energetics and Mitochondrial Dysfunction in Hypertrophic Cardiomyopathy

Background: Hypertrophic cardiomyopathy (HCM) is a complex disease partly explained by the effects of individual gene variants on sarcomeric protein biomechanics. At the cellular level, HCM mutations most commonly enhance force production, leading to higher energy demands. Despite significant advances in elucidating sarcomeric structure–function relationships, there is still much to be learned about the mechanisms that link altered cardiac energetics to HCM phenotypes. Here, we test the hypothesis that changes in cardiac energetics represent a common pathophysiologic pathway in HCM. Methods: We performed a comprehensive multiomics profile of the molecular (transcripts, metabolites, and complex lipids), ultrastructural, and functional components of HCM energetics using myocardial samples from 27 HCM patients and 13 normal controls (donor hearts). Results: Integrated omics analysis revealed alterations in a wide array of biochemical pathways with major dysregulation in fatty acid metabolism, reduction of acylcarnitines, and accumulation of free fatty acids. HCM hearts showed evidence of global energetic decompensation manifested by a decrease in high energy phosphate metabolites (ATP, ADP, and phosphocreatine) and a reduction in mitochondrial genes involved in creatine kinase and ATP synthesis. Accompanying these metabolic derangements, electron microscopy showed an increased fraction of severely damaged mitochondria with reduced cristae density, coinciding with reduced citrate synthase activity and mitochondrial oxidative respiration. These mitochondrial abnormalities were associated with elevated reactive oxygen species and reduced antioxidant defenses. However, despite significant mitochondrial injury, HCM hearts failed to upregulate mitophagic clearance. Conclusions: Overall, our findings suggest that perturbed metabolic signaling and mitochondrial dysfunction are common pathogenic mechanisms in patients with HCM. These results highlight potential new drug targets for attenuation of the clinical disease through improving metabolic function and reducing mitochondrial injury.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Genome-wide profiling of histone (H3) lysine 4 (K4) tri-methylation (me3) under drought, heat, and combined stresses in switchgrass

Background: Switchgrass (Panicum virgatum L.) is a warm-season perennial (C4) grass identified as an important biofuel crop in the United States. It is well adapted to the marginal environment where heat and moisture stresses predominantly affect crop growth. However, the underlying molecular mechanisms associated with heat and drought stress tolerance still need to be fully understood in switchgrass. The methylation of H3K4 is often associated with transcriptional activation of genes, including stress-responsive. Therefore, this study aimed to analyze genome-wide histone H3K4-tri-methylation in switchgrass under heat, drought, and combined stress. Results: In total, ~ 1.3 million H3K4me3 peaks were identified in this study using SICER. Among them, 7,342; 6,510; and 8,536 peaks responded under drought (DT), drought and heat (DTHT), and heat (HT) stresses, respectively. Most DT and DTHT peaks spanned 0 to + 2000 bases from the transcription start site [TSS]. By comparing differentially marked peaks with RNA-Seq data, we identified peaks associated with genes: 155 DT-responsive peaks with 118 DT-responsive genes, 121 DTHT-responsive peaks with 110 DTHT-responsive genes, and 175 HT-responsive peaks with 136 HT-responsive genes. We have identified various transcription factors involved in DT, DTHT, and HT stresses. Gene Ontology analysis using the AgriGO revealed that most genes belonged to biological processes. Most annotated peaks belonged to metabolite interconversion, RNA metabolism, transporter, protein modifying, defense/immunity, membrane traffic protein, transmembrane signal receptor, and transcriptional regulator protein families. Further, we identified significant peaks associated with TFs, hormones, signaling, fatty acid and carbohydrate metabolism, and secondary metabolites. qRT-PCR analysis revealed the relative expressions of six abiotic stress-responsive genes (transketolase, chromatin remodeling factor-CDH3, fatty-acid desaturase A, transmembrane protein 14C, beta-amylase 1, and integrase-type DNA binding protein genes) that were significantly (P < 0.05) marked during drought, heat, and combined stresses by comparing stress-induced against un-stressed and input controls. Conclusion: Our study provides a comprehensive and reproducible epigenomic analysis of drought, heat, and combined stress responses in switchgrass. Significant enrichment of H3K4me3 peaks downstream of the TSS of protein-coding genes was observed. In addition, the cost-effective experimental design, modified ChIP-Seq approach, and analyses presented here can serve as a prototype for other non-model plant species for conducting stress studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Mechanisms of metabolic adaptation in the duckweed Lemna gibba: an integrated metabolic, transcriptomic and flux analysis

Abstract Background Duckweeds are small, rapidly growing aquatic flowering plants. Due to their ability for biomass production at high rates they represent promising candidates for biofuel feedstocks. Duckweeds are also excellent model organisms because they can be maintained in well-defined liquid media, usually reproduce asexually, and because genomic resources are becoming increasingly available. To demonstrate the utility of duckweed for integrated metabolic studies, we examined the metabolic adaptation of growing Lemna gibba cultures to different nutritional conditions. Results To establish a framework for quantitative metabolic research in duckweeds we derived a central carbon metabolism network model of Lemna gibba based on its draft genome. Lemna gibba fronds were grown with nitrate or glutamine as nitrogen source. The two conditions were compared by quantification of growth kinetics, metabolite levels, transcript abundance, as well as by 13 C-metabolic flux analysis. While growing with glutamine, the fronds grew 1.4 times faster and accumulated more protein and less cell wall components compared to plants grown on nitrate. Characterization of photomixotrophic growth by 13 C-metabolic flux analysis showed that, under both metabolic growth conditions, the Calvin-Benson-Bassham cycle and the oxidative pentose-phosphate pathway are highly active, creating a futile cycle with net ATP consumption. Depending on the nitrogen source, substantial reorganization of fluxes around the tricarboxylic acid cycle took place, leading to differential formation of the biosynthetic precursors of the Asp and Gln families of proteinogenic amino acids. Despite the substantial reorganization of fluxes around the tricarboxylic acid cycle, flux changes could largely not be associated with changes in transcripts. Conclusions Through integrated analysis of growth rate, biomass composition, metabolite levels, and metabolic flux, we show that Lemna gibba is an excellent system for quantitative metabolic studies in plants. Our study showed that Lemna gibba adjusts to different nitrogen sources by reorganizing central metabolism. The observed disconnect between gene expression regulation and metabolism underscores the importance of metabolic flux analysis as a tool in such studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Pyrophosphate-free glycolysis in Clostridium thermocellum increases both thermodynamic driving force and ethanol titers

Background: Clostridium thermocellum is a promising candidate for production of cellulosic biofuels, however, its final product titer is too low for commercial application, and this may be due to thermodynamic limitations in glycolysis. Previous studies in this organism have revealed a metabolic bottleneck at the phosphofructokinase (PFK) reaction in glycolysis. In the wild-type organism, this reaction uses pyrophosphate (PP i ) as an energy cofactor, which is thermodynamically less favorable compared to reactions that use ATP as a cofactor. Previously we showed that replacing the PP i -linked PFK reaction with an ATP-linked reaction increased the thermodynamic driving force of glycolysis, but only had a local effect on intracellular metabolite concentrations, and did not affect final ethanol titer. Results: In this study, we substituted PP i -pfk with ATP-pfk, deleted the other PPi-requiring glycolytic gene pyruvate:phosphate dikinase (ppdk), and expressed a soluble pyrophosphatase (PPase) and pyruvate kinase (pyk) genes to engineer PP i -free glycolysis in C. thermocellum. We demonstrated a decrease in the reversibility of the PFK reaction, higher levels of lower glycolysis metabolites, and an increase in ethanol titer by an average of 38% (from 15.1 to 21.0 g/L) by using PP i -free glycolysis. Conclusions: By engineering PP i -free glycolysis in C. thermocellum, we achieved an increase in ethanol production. These results demonstrate that optimizing the thermodynamic landscape through metabolic engineering can enhance product titers. While further increases in ethanol titers are necessary for commercial application, this work represents a significant step toward engineering glycolysis in C. thermocellum to increase ethanol titers.

09 BIOMASS FUELS↗
DOE OSTI2022

METABOLIC: high-throughput profiling of microbial genomes for functional traits, metabolism, biogeochemistry, and community-scale functional networks

Background Advances in microbiome science are being driven in large part due to our ability to study and infer microbial ecology from genomes reconstructed from mixed microbial communities using metagenomics and single-cell genomics. Such omics-based techniques allow us to read genomic blueprints of microorganisms, decipher their functional capacities and activities, and reconstruct their roles in biogeochemical processes. Currently available tools for analyses of genomic data can annotate and depict metabolic functions to some extent; however, no standardized approaches are currently available for the comprehensive characterization of metabolic predictions, metabolite exchanges, microbial interactions, and microbial contributions to biogeochemical cycling. Results We present METABOLIC (METabolic And BiogeOchemistry anaLyses In miCrobes), a scalable software to advance microbial ecology and biogeochemistry studies using genomes at the resolution of individual organisms and/or microbial communities. The genome-scale workflow includes annotation of microbial genomes, motif validation of biochemically validated conserved protein residues, metabolic pathway analyses, and calculation of contributions to individual biogeochemical transformations and cycles. The community-scale workflow supplements genome-scale analyses with determination of genome abundance in the microbiome, potential microbial metabolic handoffs and metabolite exchange, reconstruction of functional networks, and determination of microbial contributions to biogeochemical cycles. METABOLIC can take input genomes from isolates, metagenome-assembled genomes, or single-cell genomes. Results are presented in the form of tables for metabolism and a variety of visualizations including biogeochemical cycling potential, representation of sequential metabolic transformations, community-scale microbial functional networks using a newly defined metric “MW-score” (metabolic weight score), and metabolic Sankey diagrams. METABOLIC takes ~ 3 h with 40 CPU threads to process ~ 100 genomes and corresponding metagenomic reads within which the most compute-demanding part of hmmsearch takes ~ 45 min, while it takes ~ 5 h to complete hmmsearch for ~ 3600 genomes. Tests of accuracy, robustness, and consistency suggest METABOLIC provides better performance compared to other software and online servers. To highlight the utility and versatility of METABOLIC, we demonstrate its capabilities on diverse metagenomic datasets from the marine subsurface, terrestrial subsurface, meadow soil, deep sea, freshwater lakes, wastewater, and the human gut. Conclusion METABOLIC enables the consistent and reproducible study of microbial community ecology and biogeochemistry using a foundation of genome-informed microbial metabolism, and will advance the integration of uncultivated organisms into metabolic and biogeochemical models. METABOLIC is written in Perl and R and is freely available under GPLv3 at https://github.com/AnantharamanLab/METABOLIC.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Conformational heterogeneity in the dGsw purine riboswitch: role of Mg²⁺ and 2’-dG in aptamer folding

Recent advancements in RNA structural biology have focused on unraveling the complexities of non-coding mRNA elements like riboswitches. These cis-acting regulatory regions undergo structural changes in response to specific cellular metabolites, leading to up or downregulation of downstream genes. The purine riboswitch family regulates many prokaryotic genes involved in purine degradation and biosynthesis. They feature an aptamer domain organized around a 3-way helical junction, where ligand encapsulation occurs at the junctional core. In our study, we chemically probed the aptamer domain of the 2’-dG-sensing purine riboswitch from Mesoplasma florum (dGsw) under various solution conditions to understand how Mg²⁺ and 2’-dG influence riboswitch folding. Here, we find that efficient 2’-dG binding strongly depends on Mg²⁺, indicating that Mg²⁺ is essential for priming dGsw for ligand interactions. We identified a previously undescribed sequence in the 5’ tail of dGsw that is complementary to a conserved helix. The inclusion of this region in a construct led to intramolecular competition between the alternate helix, Palt, and P1. Mutational analysis confirmed that 5’ flanking end of the aptamer domain forms an alternate helix in the absence of ligand. Molecular dynamics simulations revealed that this alternative conformation is stable. This helix may, therefore, facilitate the formation of an anti-terminator helix by opening the 3-way junction surrounding the 2’-dG binding site. Our study further establishes the importance of a closed terminal P1 helix conformation for metabolite binding and suggests that the delicate interplay between P1 and Palt may fine-tune downstream gene regulation. These insights offer a new perspective on riboswitch structure and enhance our understanding of the role that a conformational ensemble plays in riboswitch activity and regulation.

Biochemistry & Molecular Biology↗
DOE OSTI2026

Data for Expression of a Bacterial Trehalose 6-Phosphate Synthase Gene otsA in Camelina sativa Seeds Promotes the Channelling of Carbon Towards Oil Accumulation

Improving seed oil yield is essential for developing Camelina sativa as a sustainable biofuel crop. Fatty acid synthesis depends on the production of acetyl-CoA from photosynthetically derived sugars. Trehalose 6-phosphate (T6P), a proxy for sucrose availability, can link sugar status to plant growth and development. Synthesised by trehalose 6-phosphate synthase (TPS) from UDP-glucose and glucose-6-phosphate, T6P plays a regulatory role in metabolism. Our previous studies on Arabidopsis transgenic lines constitutively expressing the E. coli otsA (encoding TPS) showed increased T6P levels and seed triacylglycerol, along with stunted growth. In the present study we express otsA in camelina under the control of a seed-specific Phaseolin promoter. Seeds of the resulting transgenic lines accumulated high levels of T6P, and a 15%–20% increase in total fatty acids and triacylglycerol compared to wild-type. Molecular analysis showed the transgenic seeds had reduced SnRK1 activity, elevated WRI1 protein levels, and increased the levels of WRI1 and its target genes, along with enhanced rates of fatty acid synthesis that increased seed weights relative to wild type. Notably, the increase in oil did not affect seed protein levels but did reduce the soluble metabolite fraction. Crucially, seed-specific expression of otsA mitigated the growth defects associated with constitutive otsA expression, and the transgenic lines showed normal seed development and germination. These findings demonstrate that targeted T6P modulation via seed-specific otsA expression is an effective metabolic engineering strategy to boost oil production in camelina and potentially in other oilseed crops and bioenergy crops such as energycane, sorghum and miscanthus.

Lipids↗