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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Hyperglycemia alters mitochondrial respiration efficiency and mitophagy in human podocytes

Highlights: • Impairment of mitochondrial dynamics underlies the pathogenesis of type 2 diabetes. • Mitochondrial respiration is altered in glomeruli isolated from diabetic STZ-rats. • High glucose induces mitochondrial fission and fragmentation in human podocytes. • Mitochondrial fusion, biogenesis and mitophagy are reduced in HG-treated podocytes. • HG can injure the kidney by alteration of podocytes and glomerular bioenergetics. Podocytes constitute the outer layer of the renal glomerular filtration barrier. Their energy requirements strongly depend on efficient oxidative respiration, which is tightly connected with mitochondrial dynamics. We hypothesized that hyperglycemia modulates energy metabolism in glomeruli and podocytes and contributes to the development of diabetic kidney disease. We found that oxygen consumption rates were severely reduced in glomeruli from diabetic rats and in human podocytes that were cultured in high glucose concentration (30 mM; HG). In these models, all of the mitochondrial respiratory parameters, including basal and maximal respiration, ATP production, and spare respiratory capacity, were significantly decreased. Podocytes that were treated with HG showed a fragmented mitochondrial network, together with a decrease in expression of the mitochondrial fusion markers MFN1, MFN2, and OPA1, and an increase in the activity of the fission marker DRP1. We showed that markers of mitochondrial biogenesis, such as PGC-1α and TFAM, decreased in HG-treated podocytes. Moreover, PINK1/parkin-dependent mitophagy was inhibited in these cells. These results provide evidence that hyperglycemia impairs mitochondrial dynamics and turnover, which may underlie the remarkable deterioration of mitochondrial respiration parameters in glomeruli and podocytes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Hyporheic‐Zone Processes and Stream Oxygen Dynamics: Insights From a Multiscale Reactive Transport Model

Aquatic ecosystem metabolism encapsulates the daily fixation (gross primary production, GPP d ) and mineralization (ecosystem respiration, ER d ) of organic carbon. In fluvial systems, these are commonly estimated by inverse solutions to field observations using a model that describes oxygen concentrations varying in the water column in response to metabolic fluxes and air‐water gas exchange controlled by a rate coefficient (K 600 ). The most common conceptual model is the single‐station metabolism (SSM) model. The simplicity and flexibility of this conceptualization make it attractive; however, it implicitly assumes that all the processes that consume oxygen in fluvial systems can be lumped into a bulk estimate of respiration with poorly understood consequences for estimates of GPP d , ER d , and K 600 . Here, we focus on the implications of using SSM conceptualization when estimating metabolic fluxes from oxygen dynamics in channels where hyporheic exchange occurs. We use a new multiscale numerical model for reactive transport in streams that represents hyporheic exchange and streambed heterotrophic respiration. Nondimensionalization of this model reveals dimensionless groups that collectively control oxygen dynamics. Numerical experiments offer a mechanistic understanding of the impacts of hyporheic exchange on diel oxygen dynamics revealing that potential biases arise from neglecting mass transfer limitations. Specifically, we found that hyporheic exchange significantly affects diel oxygen dynamics, even for nonreactive streambed sediments. Moreover, while the SSM performs well in many situations, we find conditions where significant bias is produced by hyporheic exchange, even when oxygen data are well‐fitted. These situations pose a major challenge in the interpretation of metabolism assessment estimates.

Gomez‐Velez, Jesus D. [Oak Ridge National Laborato↗
DOE OSTI2022

Cell-Free Protein Synthesis for High-Throughput Biosynthetic Pathway Prototyping

Biological systems provide a sustainable and complimentary approach to synthesizing useful chemical products. Metabolic engineers seeking to establish economically viable biosynthesis platforms strive to increase product titers, rates, and yields. Despite continued advances in genetic tools and metabolic engineering techniques, cellular workflows remain limited in throughput. It may take months to test dozens of unique pathway designs even in a robust model organism, such as Escherichia coli. In contrast, cell-free protein synthesis enables the rapid generation of enzyme libraries that can be combined to reconstitute metabolic pathways in vitro for biochemical synthesis in days rather than weeks. Cell-free reactions thereby enable comparison of hundreds to thousands of unique combinations of enzyme homologs and concentrations, which can quickly identify the most productive pathway variants to test in vivo or further characterize in vitro. Furthermore, this cell-free pathway prototyping strategy provides a complementary approach to accelerate cellular metabolic engineering efforts toward highly productive strains for metabolite production.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Optode performance data associated with: Metabolic Multireactor: practical considerations for using simple oxygen sensing optodes for high-throughput batch reactor metabolism experiments

This data package is associated with the publication “Metabolic Multireactor: practical considerations for using simple oxygen sensing optodes for high-throughput batch reactor metabolism experiments”, submitted to PlosONE (Kaufman et al. 2023; 10.1101/2023.03.28.534656).We carried out many testing and calibration experiments on a system of small oxygen consumption batch reactors designed for use with water and sediment samples for environmental questions. The oxygen sensing system is based very directly on the work of Larsen, et al. [2011], and similar oxygen sensing technology is widely used in the literature. Our primary focus was on practical considerations, such as temperature effects, lighting angle effects, sterilization, and other similar situations that a user may find useful. Most of the tests required comparing “base” calibration curves to “treatment” calibration curves to determine the extent to which the treatment impacted the reported measurements. This data package contains the performance and calibration data collected for that purpose.This dataset is comprised of one data folder containing (1) file-level metadata; (2) data dictionary; (3) readme; (4) diffusion test result files; (5) limit of detection test result files; (6) temperature impact files; (7) a main data file that contains test results for all other tests; and (8) an R script that uses Kolmogorov-Smirnov tests to determine whether treatment calibrations are significantly different from their respective base calibrations. All files are .csv, .txt, .Rmd, or .pdf.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Encapsulation in a Bacterial Microcompartment Shell Improves Thermal Stability of a Glycolytic Enzyme

Selective encapsulation of target enzymes is an increasingly well-studied field, with a host of potential applications for biotechnology. Natively, many bacteria utilize bacterial microcompartments (BMCs) for enzyme encapsulation to enhance catalysis. BMCs are protein shells that enable selective localization of targeted metabolic enzymes and may improve catalytic rates by colocalizing pathway enzymes and/or serve to sequester toxic or volatile intermediates. The microcompartment shell of Haliangium ochraceum (HO) is a notable BMC chassis because of its modularity and versatility; it is easily expressed and assembled outside its native host and can accept a wide array of cargo. Recently, it was demonstrated that assembly of HO BMC shells can be easily achieved in vitro. Following up on our previous work on in vivo assembly of HO-BMCs with triose phosphate isomerase (TPI) as a model enzyme cargo, here we have demonstrated the advantages of in vitro assembly (IVA) for targeted enzyme encapsulation. We achieved variable loading of BMC shells with targeted amounts of TPI and demonstrated enhanced thermal stability of encapsulated TPI versus free TPI up to 62 °C.

assays↗
DOE OSTI2022

Lipo-Chitooligosaccharides Induce Specialized Fungal Metabolite Profiles That Modulate Bacterial Growth

Lipo-chitooligosaccharides (LCOs) are historically known for their role as microbial-derived signaling molecules that shape plant symbiosis with beneficial rhizobia or mycorrhizal fungi. Recent studies showing that LCOs are widespread across the fungal kingdom have raised questions about the ecological function of these compounds in organisms that do not form symbiotic relationships with plants. To elucidate the ecological function of these compounds, we investigate the metabolomic response of the ubiquitous human pathogen Aspergillus fumigatus to LCOs. Our metabolomics data revealed that exogenous application of various types of LCOs to A. fumigatus resulted in significant shifts in the fungal metabolic profile, with marked changes in the production of specialized metabolites known to mediate ecological interactions. Using network analyses, we identify specific types of LCOs with the most significant effect on the abundance of known metabolites. Extracts of several LCO-induced metabolic profiles significantly impact the growth rates of diverse bacterial species. These findings suggest that LCOs may play an important role in the competitive dynamics of non-plant-symbiotic fungi and bacteria. This study identifies specific metabolomic profiles induced by these ubiquitously produced chemicals and creates a foundation for future studies into the potential roles of LCOs as modulators of interkingdom competition.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Metabolic flux and resource balance in the oleaginous yeast Rhodotorula toruloides

The yeast Rhodotorula toruloides is a promising bioproduction organism due to its high lipid yields and ability to grow on cheap and abundant substrates. Quantitative, systems-level assessment of its metabolic activity is accordingly merited. Resource-balance analysis (RBA) models capture not only reaction stoichiometry but also enzyme requirements for catalysis, providing valuable tools for understanding metabolic trade-offs and optimizing metabolic engineering strategies. Here, in this work, we present systems-level measurements of R. toruloides metabolic flux based on isotope tracing and metabolic flux analysis. In combination with new proteomic measurements, these flux data are used to parameterize a genome-scale resource balance model rtRBA. We find that S. cerevisiae and R. toruloides grow at nearly indistinguishable rates using similar biosynthetic but dramatically different central metabolic programs. R. toruloides consumes one-fifth as much glucose, which it metabolizes primarily via the pentose phosphate pathway and TCA cycle unlike primarily glycolysis in S. cerevisiae . Overall, across these two divergent yeasts, protein abundances aligned more closely than metabolic flux. Resource balance modeling of these metabolic programs predicts superior theoretical yields but lower productivities in R. toruloides than S. cerevisiae for industrial chemicals, highlighting the value of rapid glucose uptake for productivity but respiratory metabolism for yields.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Mutual-information based optimal experimental design for hyperpolarized $$^{13}$$C-pyruvate MRI

Abstract A key parameter of interest recovered from hyperpolarized (HP) MRI measurements is the apparent pyruvate-to-lactate exchange rate, $$k_{{\textrm PL}}$$ k P L , for measuring tumor metabolism. This manuscript presents an information-theory-based optimal experimental design approach that minimizes the uncertainty in the rate parameter, $$k_{{\textrm PL}}$$ k P L , recovered from HP-MRI measurements. Mutual information is employed to measure the information content of the HP measurements with respect to the first-order exchange kinetics of the pyruvate conversion to lactate. Flip angles of the pulse sequence acquisition are optimized with respect to the mutual information. A time-varying flip angle scheme leads to a higher parameter optimization that can further improve the quantitative value of mutual information over a constant flip angle scheme. However, the constant flip angle scheme, 35 and 28 degrees for pyruvate and lactate measurements, leads to an accuracy and precision comparable to the variable flip angle schemes obtained from our method. Combining the comparable performance and practical implementation, optimized pyruvate and lactate flip angles of 35 and 28 degrees, respectively, are recommended.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Competitive Exclusion and Metabolic Dependency among Microorganisms Structure the Cellulose Economy of an Agricultural Soil

Microorganisms that degrade cellulose utilize extracellular reactions that yield free by-products which can promote interactions with noncellulolytic organisms. We hypothesized that these interactions determine the ecological and physiological traits governing the fate of cellulosic carbon (C) in soil. We performed comparative genomics with genome bins from a shotgun metagenomic-stable isotope probing experiment to characterize the attributes of cellulolytic and noncellulolytic taxa accessing 13 C from cellulose. We hypothesized that cellulolytic taxa would exhibit competitive traits that limit access, while noncellulolytic taxa would display greater metabolic dependency, such as signatures of adaptive gene loss. We tested our hypotheses by evaluating genomic traits indicative of competitive exclusion or metabolic dependency, such as antibiotic production, growth rate, surface attachment, biomass degrading potential, and auxotrophy. The most 13 C-enriched taxa were cellulolytic Cellvibrio (Gammaproteobacteria) and Chaetomium (Ascomycota), which exhibited a strategy of self-sufficiency (prototrophy), rapid growth, and competitive exclusion via antibiotic production. Auxotrophy was more prevalent in cellulolytic Actinobacteria than in cellulolytic Proteobacteria, demonstrating differences in dependency among cellulose degraders. Noncellulolytic taxa that accessed 13 C from cellulose (Planctomycetales, Verrucomicrobia, and Vampirovibrionales) were also more dependent, as indicated by patterns of auxotrophy and 13 C labeling (i.e., partial labeling or labeling at later stages). Major 13 C-labeled cellulolytic microbes (e.g., Sorangium, Actinomycetales, Rhizobiales, and Caulobacteraceae) possessed adaptations for surface colonization (e.g., gliding motility, hyphae, attachment structures) signifying the importance of surface ecology in decomposing particulate organic matter. Our results demonstrated that access to cellulosic C was accompanied by ecological trade-offs characterized by differing degrees of metabolic dependency and competitive exclusion.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

SNPeffect: identifying functional roles of SNPs using metabolic networks

Genetic sources of phenotypic variation have been a focus of plant studies aimed at improving agricultural yield and understanding adaptive processes. Genome-wide association studies identify the genetic background behind a trait by examining associations between phenotypes and single-nucleotide polymorphisms (SNPs). Although such studies are common, biological interpretation of the results remains a challenge; especially due to the confounding nature of population structure and the systematic biases thus introduced. Here, we propose a complementary analysis (SNPeffect) that offers putative genotype-to-phenotype mechanistic interpretations by integrating biochemical knowledge encoded in metabolic models. SNPeffect is used to explain differential growth rate and metabolite accumulation in A. thaliana and P. trichocarpa accessions as the outcome of SNPs in enzyme-coding genes. To this end, we also constructed a genome-scale metabolic model for Populus trichocarpa, the first for a perennial woody tree. As expected, our results indicate that growth is a complex polygenic trait governed by carbon and energy partitioning. The predicted set of functional SNPs in both species are associated with experimentally characterized growth-determining genes and also suggest putative ones. Functional SNPs were found in pathways such as amino acid metabolism, nucleotide biosynthesis, and cellulose and lignin biosynthesis, in line with breeding strategies that target pathways governing carbon and energy partition.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

TranSyT , an innovative framework for identifying transport systems

The importance and rate of development of genome-scale metabolic models have been growing for the last few years, increasing the demand for software solutions that automate several steps of this process. However, since TRIAGE’s release, software development for the automatic integration of transport reactions into models has stalled. Here, in this paper, we present the Transport Systems Tracker (TranSyT). Unlike other transport systems annotation software, TranSyT does not rely on manual curation to expand its internal database, which is derived from highly curated records retrieved from the Transporters Classification Database and complemented with information from other data sources. TranSyT compiles information regarding transporter families and proteins, and derives reactions into its internal database, making it available for rapid annotation of complete genomes. All transport reactions have GPR associations and can be exported with identifiers from four different metabolite databases. TranSyT is currently available as a plugin for merlin v4.0 and an app for KBase.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Creating yellow seed Camelina sativa with enhanced oil accumulation by CRISPR ‐mediated disruption of Transparent Testa 8

Summary Camelina ( Camelina sativa L.), a hexaploid member of the Brassicaceae family, is an emerging oilseed crop being developed to meet the increasing demand for plant oils as biofuel feedstocks. In other Brassicas, high oil content can be associated with a yellow seed phenotype, which is unknown for camelina. We sought to create yellow seed camelina using CRISPR/Cas9 technology to disrupt its Transparent Testa 8 (TT8) transcription factor genes and to evaluate the resulting seed phenotype. We identified three TT8 genes, one in each of the three camelina subgenomes, and obtained independent CsTT8 lines containing frameshift edits. Disruption of TT8 caused seed coat colour to change from brown to yellow reflecting their reduced flavonoid accumulation of up to 44%, and the loss of a well‐organized seed coat mucilage layer. Transcriptomic analysis of CsTT8 ‐edited seeds revealed significantly increased expression of the lipid‐related transcription factors LEC1 , LEC2 , FUS3 , and WRI1 and their downstream fatty acid synthesis‐related targets. These changes caused metabolic remodelling with increased fatty acid synthesis rates and corresponding increases in total fatty acid (TFA) accumulation from 32.4% to as high as 38.0% of seed weight, and TAG yield by more than 21% without significant changes in starch or protein levels compared to parental line. These data highlight the effectiveness of CRISPR in creating novel enhanced‐oil germplasm in camelina. The resulting lines may directly contribute to future net‐zero carbon energy production or be combined with other traits to produce desired lipid‐derived bioproducts at high yields.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Shrub and sedge rhizosphere communities display distinct affinities toward exudates and soil organic matter degradation: a quantitative stable isotope probing analysis

Warming temperatures are accelerating permafrost thaw and changing tundra vegetation, where woody shrubs are displacing sedges. Shrubs, such as Betula nana, and sedges, such as Eriophorum vaginatum, exhibit distinct life strategies including unique root-associated, or rhizosphere microbial communities. As permafrost thaws it unlocks previously unavailable carbon and nutrient sources resulting in deeper roots and a translocation of rhizosphere communities. Because permafrost microbial communities contain lower diversity and biomass than rhizosphere communities, the coalescence of rhizosphere and permafrost microbial communities could alter soil organic matter (SOM) degradation rates and increase greenhouse gas emissions. To identify metabolic strategies across distinct rhizosphere and permafrost microbial communities we conducted an isotope tracing incubation experiment. We inoculated thawed permafrost with shrub and sedge rhizosphere communities while adding exudates or water daily and compared this to an uninoculated control. After 46 days, we spiked samples with 18O enriched water or 13C enriched exudates and measured isotope incorporation into microbial DNA with quantitative stable isotope probing (qSIP). Our results indicate that exudate additions had little effect on uninoculated permafrost communities but the addition of exudates and rhizosphere inoculants had a compounding effect on respiration rates. We found that soils inoculated with shrub rhizosphere communities contained a mixture of exudate and SOM degraders while soils inoculated with sedge rhizosphere communities contained mainly SOM degraders. Finally, we found that individual microbial taxa exhibited maximum growth rates under specific combinations of microbial inoculant communities and exudate addition treatments. Our results reveal that microbial niches are strongly influenced by substrate preferences and community context, and suggest that a reduction in sedges and an expansion of shrubs may provide a mechanism by which permafrost carbon losses are mitigated through corresponding shifts in microbial communities and their substrate preferences.

Schaefer, Sean R [Natural Resources and Earth Syst↗
DOE OSTI2021

Crabtree/Warburg-like aerobic xylose fermentation by engineered Saccharomyces cerevisiae

Bottlenecks in the efficient conversion of xylose into cost-effective biofuels have limited the widespread use of plant lignocellulose as a renewable feedstock. The yeast Saccharomyces cerevisiae ferments glucose into ethanol with such high metabolic flux that it ferments high concentrations of glucose aerobically, a trait called the Crabtree/Warburg Effect. In contrast to glucose, most engineered S. cerevisiae strains do not ferment xylose at economically viable rates and yields, and they require respiration to achieve sufficient xylose metabolic flux and energy return for growth aerobically. Here, we evolved respiration-deficient S. cerevisiae strains that can grow on and ferment xylose to ethanol aerobically, a trait analogous to the Crabtree/Warburg Effect for glucose. Through genome sequence comparisons and directed engineering, we determined that duplications of genes encoding engineered xylose metabolism enzymes, as well as TKL1, a gene encoding a transketolase in the pentose phosphate pathway, were the causative genetic changes for the evolved phenotype. Reengineered duplications of these enzymes, in combination with deletion mutations in HOG1, ISU1, GRE3, and IRA2, increased the rates of aerobic and anaerobic xylose fermentation. Importantly, we found that these genetic modifications function in another genetic background and increase the rate and yield of xylose-to-ethanol conversion in industrially relevant switchgrass hydrolysate, indicating that these specific genetic modifications may enable the sustainable production of industrial biofuels from yeast. We propose a model for how key regulatory mutations prime yeast for aerobic xylose fermentation by lowering the threshold for overflow metabolism, allowing mutations to increase xylose flux and to redirect it into fermentation products.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Carbon Negative Synthesis of Amino Acids Using a Cell-Free-Based Biocatalyst

Biological systems can directly upgrade carbon dioxide (CO 2 ) into chemicals. The CO 2 fixation rate of autotrophic organisms, however, is too slow for industrial utility, and the breadth of engineered metabolic pathways for the synthesis of value-added chemicals is too limited. Biotechnology workhorse organisms with extensively engineered metabolic pathways have recently been engineered for CO 2 fixation. Yet, their low carbon fixation rate, compounded by the fact that living organisms split their carbon between cell growth and chemical synthesis, has led to only cell growth with no chemical synthesis achieved to date. Here, we engineer a lysate-based cell-free expression (CFE)-based multienzyme biocatalyst for the carbon negative synthesis of the industrially relevant amino acids glycine and serine from CO 2 equivalents–formate and bicarbonate–and ammonia. The formate-to-serine biocatalyst leverages tetrahydrofolate (THF)-dependent formate fixation, reductive glycine synthesis, serine synthesis, and phosphite dehydrogenase-dependent NAD(P)H regeneration to convert 30% of formate into serine and glycine, surpassing the previous 22% conversion using a purified enzyme system. We find that (1) the CFE-based biocatalyst is active even after 200-fold dilution, enabling higher substrate loading and product synthesis without incurring additional cell lysate cost, (2) NAD(P)H regeneration is pivotal to driving forward reactions close to thermodynamic equilibrium, (3) balancing the ratio of the formate-to-serine pathway genes added to the CFE is key to improving amino acid synthesis, and (4) efficient THF recycling enables lowering the loading of this cofactor, reducing the cost of the CFE-based biocatalyst. To our knowledge, this is the first synthesis of amino acids that can capture CO 2 equivalents for the carbon negative synthesis of amino acids using a CFE-based biocatalyst. Looking ahead, the CFE-based biocatalyst process could be extended beyond serine to pyruvate, a key intermediate, to access a variety of chemicals from aromatics and terpenes to alcohols and polymers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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 OSTI2022

Integrated flux and pool size analysis in plant central metabolism reveals unique roles of glycine and serine during photorespiration

Photorespiration is an essential process juxtaposed between plant carbon and nitrogen metabolism that responds to dynamic environments. Photorespiration recycles inhibitory intermediates arising from oxygenation reactions catalysed by Rubisco back into the C 3 cycle, but it is unclear what proportions of its nitrogen-containing intermediates (glycine and serine) are exported into other metabolisms in vivo and how these pool sizes affect net CO 2 gas exchange during photorespiratory transients. Here, to address this uncertainty, we measured rates of amino acid export from photorespiration using isotopically non-stationary metabolic flux analysis. This analysis revealed that ~23–41% of the photorespiratory carbon was exported from the pathway as serine under various photorespiratory conditions. Furthermore, we determined that the build-up and relaxation of glycine pools constrained a large portion of photosynthetic acclimation during photorespiratory transients. Furthermore, these results reveal the unique and important roles of glycine and serine in successfully maintaining various photorespiratory fluxes that occur under environmental fluctuations in nature and providing carbon and nitrogen for metabolism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Ecological and genomic responses of soil microbiomes to high-severity wildfire: linking community assembly to functional potential

Increasing wildfire severity, which is common throughout the western United States, can have deleterious effects on plant regeneration and large impacts on carbon (C) and nitrogen (N) cycling rates. Soil microbes are pivotal in facilitating these elemental cycles, so understanding the impact of increasing fire severity on soil microbial communities is critical. Here, we assess the long-term impact of high-severity fires on the soil microbiome. We find that high-severity wildfires result in a multi-decadal (>25 y) recovery of the soil microbiome mediated by concomitant differences in aboveground vegetation, soil chemistry, and microbial assembly processes. Our results depict a distinct taxonomic and functional successional pattern of increasing selection in post-fire soil microbial communities. Changes in microbiome composition corresponded with changes in microbial functional potential, specifically altered C metabolism and enhanced N cycling potential, which related to rates of potential decomposition and inorganic N availability, respectively. Based on metagenome-assembled genomes, we show that bacterial genomes enriched in our earliest site (4 y since fire) harbor distinct traits such as a robust stress response and a high potential to degrade pyrogenic, polyaromatic C that allow them to thrive in post-fire environments. Taken together, these results provide a biological basis for previously reported process rate measurements and explain the temporal dynamics of post-fire biogeochemistry, which ultimately constrains ecosystem recovery.

59 BASIC BIOLOGICAL SCIENCES↗