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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

The Influence of Bacteria on the Growth, Lipid Production, and Extracellular Metabolite Accumulation by Phaeodactylum tricornutum (Bacillariophyceae)

Here, to examine the impact of heterotrophic bacteria on microalgal physiology, we co-cultured the diatom Phaeodactylum tricornutum with six bacterial strains to quantify bacteria-mediated differences in algal biomass, total intracellular lipids, and for a subset, extracellular metabolite accumulation. A Marinobacter isolate significantly increased algal cell concentrations, dry biomass, and lipid content compared to axenic algal cultures. Two other bacterial strains from the Bacteroidetes order, of the genera Algoriphagus and Muricauda, significantly lowered P. tricornutum biomass, leading to overall decreased lipid accumulation. These three bacterial co-cultures (one mutualistic, two competitive) were analyzed for extracellular metabolites via untargeted liquid chromatography mass spectrometry to compare against bacteria-free cultures. Over 80% of the extracellular metabolites differentially abundant in at least one treatment were in higher concentrations in the axenic cultures, in agreement with the hypothesis that the co-cultured bacteria incorporated algal-derived organic compounds for growth. Furthermore, the extracellular metabolite profiles of the two growth-inhibiting cultures were more similar to one another than the growth-promoting co-culture, linking metabolite patterns to ecological role. Our results show that algal–bacterial interactions can influence the accumulation of intracellular lipids and extracellular metabolites, and suggest that utilization and accumulation of compounds outside the cell play a role in regulating microbial interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Rapid screening of secondary aromatic metabolites in Populus trichocarpa leaves

Abstract Background High-throughput metabolomics analytical methodology is needed for population-scale studies of bioenergy-relevant feedstocks such as poplar ( Populus sp.). Here, the authors report the relative abundance of extractable aromatic metabolites in Populus trichocarpa leaves rapidly estimated using pyrolysis-molecular beam mass spectrometry (py-MBMS). Poplar leaves were analyzed in conjunction with and validated by GC/MS analysis of extracts to determine key spectral features used to build PLS models to predict the relative composition of extractable aromatic metabolites in whole poplar leaves. Results The Pearson correlation coefficient for the relative abundance of extractable aromatic metabolites based on ranking between GC/MS analysis and py-MBMS analysis of the Boardman leaf set was 0.86 with R 2 = 0.76 using a simplified prediction approach from select ions in MBMS spectra. Metabolites most influential to py-MBMS spectral features in the Clatskanie set included the following compounds: catechol, salicortin, salicyloyl-coumaroyl-glucoside conjugates, α-salicyloylsalicin, tremulacin, as well as other salicylates, trichocarpin, salicylic acid, and various tremuloidin conjugates. Ions in py-MBMS spectra with the highest correlation to the abundance of extractable aromatic metabolites as determined by GC/MS analysis of extracts, included m/z 68, 71, 77, 91, 94, 105, 107, 108, and 122, and were used to develop the simplified prediction approach without PLS models or a priori measurements. Conclusions The simplified py-MBMS method is capable of rapidly screening leaf tissue for relative abundance of extractable aromatic secondary metabolites to enable prioritization of samples in large populations requiring comprehensive metabolomics that will ultimately inform plant systems biology models and advance the development of optimized biomass feedstocks for renewable fuels and chemicals.

09 BIOMASS FUELS↗
DOE OSTI2022

Chemotaxonomic patterns in intracellular metabolites of marine microbial plankton

Most biological diversity on Earth is contained within microbial communities. In the ocean, these communities dominate processes related to carbon fixation and nutrient recycling. Yet, specific factors that determine community composition and metabolic activity are difficult to resolve in complex microbial populations, complicating predictions of microbial processes in a changing ocean. Microbial metabolism generates small organic molecules that reflect both the biochemical and physiological diversity as well as the taxonomic specificity of these biological processes. These small molecules serve as the conduit for taxon-specific signaling and exchange. Here, we use liquid chromatography-mass spectrometry (LC-MS)-based metabolomics to taxonomically categorize 111 metabolites that include small molecules in central and secondary metabolism across 42 taxa representing numerically dominant and metabolically important lineages of microbial autotrophs and heterotrophs. Patterns in metabolite presence-absence broadly reflected taxonomic lineages. A subset of metabolites that includes osmolytes, sulfur-containing metabolites, sugars, and amino acid derivatives provided chemotaxonomic information among phytoplankton taxa. A variety of phytohormones and signaling molecules were predominantly found in the heterotrophic bacteria and archaea, expanding knowledge of metabolites implicated in modulating interactions between microbes. This chemotaxonomic inventory of marine microbial metabolites is a key step in deciphering metabolic networks that influence ocean biogeochemical cycles.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Photosynthetic Electron Flows and Networks of Metabolite Trafficking to Sustain Metabolism in Photosynthetic Systems

Photosynthetic eukaryotes have metabolic pathways that occur in distinct subcellular compartments. However, because metabolites synthesized in one compartment, including fixed carbon compounds and reductant generated by photosynthetic electron flows, may be integral to processes in other compartments, the cells must efficiently move metabolites among the different compartments. This review examines the various photosynthetic electron flows used to generate ATP and fixed carbon and the trafficking of metabolites in the green alga Chlamydomomas reinhardtii; information on other algae and plants is provided to add depth and nuance to the discussion. We emphasized the trafficking of metabolites across the envelope membranes of the two energy powerhouse organelles of the cell, the chloroplast and mitochondrion, the nature and roles of the major mobile metabolites that move among these compartments, and the specific or presumed transporters involved in that trafficking. These transporters include sugar-phosphate (sugar-P)/inorganic phosphate (Pi) transporters and dicarboxylate transporters, although, in many cases, we know little about the substrate specificities of these transporters, how their activities are regulated/coordinated, compensatory responses among transporters when specific transporters are compromised, associations between transporters and other cellular proteins, and the possibilities for forming specific ‘megacomplexes’ involving interactions between enzymes of central metabolism with specific transport proteins. Finally, we discuss metabolite trafficking associated with specific biological processes that occur under various environmental conditions to help to maintain the cell’s fitness. These processes include C4 metabolism in plants and the carbon concentrating mechanism, photorespiration, and fermentation metabolism in algae.

Plant Sciences↗
DOE OSTI2021

Liquid Chromatography Coupled to Refractive Index or Mass Spectrometric Detection for Metabolite Profiling in Lysate-based Cell-free Systems

Engineering cellular metabolism for targeted biosynthesis can require extensive design-build-test-learn (DBTL) cycles as the engineer works around the cell's survival requirements. Alternatively, carrying out DBTL cycles in cell-free environments can accelerate this process and alleviate concerns with host compatibility. A promising approach to cell-free metabolic engineering (CFME) leverages metabolically active crude cell extracts as platforms for biomanufacturing and for rapidly discovering and prototyping modified proteins and pathways. Realizing these capabilities and optimizing CFME performance requires methods to characterize the metabolome of lysate-based cell-free platforms. That is, analytical tools are necessary for monitoring improvements in targeted metabolite conversions and in elucidating alterations to metabolite flux when manipulating lysate metabolism. In this work, metabolite analyses using high-performance liquid chromatography (HPLC) coupled with either optical or mass spectrometric detection were applied to characterize metabolite production and flux in E. coli S30 lysates. Specifically, this report describes the preparation of samples from CFME lysates for HPLC analyses using refractive index detection (RID) to quantify the generation of central metabolic intermediates and by-products in the conversion of low-cost substrates (i.e., glucose) to various high-value products. The analysis of metabolite conversion in CFME reactions fed with 13 C-labeled glucose through reversed-phase liquid chromatography coupled to tandem mass spectrometry (MS/MS), a powerful tool for characterizing specific metabolite yields and lysate metabolic flux from starting materials, is also presented. Altogether, applying these analytical methods to CFME lysate metabolism enables the advancement of these systems as alternative platforms for executing faster or novel metabolic engineering tasks.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

New approaches to secondary metabolite discovery from anaerobic gut microbes

The animal gut microbiome is a complex system of diverse, predominantly anaerobic microbiota with secondary metabolite potential. These metabolites likely play roles in shaping microbial community membership and influencing animal host health. As such, novel secondary metabolites from gut microbes hold significant biotechnological and therapeutic interest. Despite their potential, gut microbes are largely untapped for secondary metabolites, with gut fungi and obligate anaerobes being particularly under-explored. To advance understanding of these metabolites, culture-based and (meta)genome-based approaches are essential. Culture-based approaches enable isolation, cultivation, and direct study of gut microbes, and (meta)genome-based approaches utilize in silico tools to mine biosynthetic gene clusters (BGCs) from microbes that have not yet been successfully cultured. In this mini-review, we highlight recent innovations in this area, including anaerobic biofoundries like ExFAB, the NSF BioFoundry for Extreme & Exceptional Fungi, Archaea, and Bacteria. These facilities enable high-throughput workflows to study oxygen-sensitive microbes and biosynthetic machinery. Such recent advances promise to improve our understanding of the gut microbiome and its secondary metabolism.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A review on bacteria-derived antioxidant metabolites: their production, purification, characterization, potential applications, and limitations

Abstract Antioxidants are organic molecules that scavenge reactive oxygen species (ROS) and reactive nitrogen species (RNS), thereby maintaining cellular redox balance in living organisms. The human body synthesizes endogenous antioxidants, whereas humans obtain exogenous antioxidants from other organisms such as plants, animals, fungi, and bacteria. This review primarily focuses on the antioxidant potential of natural metabolites and extracts from five major bacterial phyla, including the well-studiedActinobacteriaandCyanobacteria, as well as less-studiedBacteroides,Firmicutes, andProteobacteria.The literature survey revealed that the metabolites and the extracts with antioxidant activity can be obtained from bacterial cells and their culture supernatants. The metabolites with antioxidant activity include pigments, phycobiliproteins, polysaccharides, mycosporins-like amino acids, peptides, phenolic compounds, and alkaloids. Both metabolites and extracts demonstrate in vitro antioxidant capacity through radical-scavenging, metal-reducing, and metal-chelating activity assays. In in vivo models, they can scavenge ROS and RNS directly and/or indirectly eliminate them by enhancing the activities of antioxidant enzymes, such as catalase, superoxide dismutase, and glutathione peroxidase. Due to their antioxidant activities, they may find applications in the cosmetic industry as anti-aging agents for the skin and in medicine as drugs or supplements for combating oxidative stress-related disorders, such as neurodegenerative diseases and diabetes. The literature survey also elucidated that some metabolites and extracts with antioxidant activity also exhibited strong antimicrobial properties. Therefore, we consider that they may have future applications in the treatment of infectious diseases, the preparation of pathogen-free healthy foods, and the extension of food shelf life.

Pharmacology & Pharmacy↗
DOE OSTI2021

Translating dosimetry of Dibenzo[ def,p ]chrysene (DBC) and metabolites across dose and species using physiologically based pharmacokinetic (PBPK) modeling

We report that Dibenzo[def,p]chrysene (DBC) is an environmental polycyclic aromatic hydrocarbon (PAH) that causes tumors in mice and has been classified as a probable human carcinogen by the International Agency for Research on Cancer. Animal toxicity studies often utilize higher doses than are found in relevant human exposures. Additionally, like many PAHs, DBC requires metabolic bioactivation to form the ultimate toxicant, and species differences in DBC and DBC metabolite metabolism have been observed. To understand the implications of dose and species differences, a physiologically based pharmacokinetic model (PBPK) for DBC and major metabolites was developed in mice and humans. Metabolism parameters used in the model were obtained from experimental in vitro metabolism assays using mice and human hepatic microsomes. PBPK model simulations were evaluated against mice dosed with 15 mg/kg DBC by oral gavage and human volunteers orally microdosed with 29 ng of DBC. DBC and its primary metabolite DBC-11,12-diol were measured in blood of mice and humans, while in urine, the majority of DBC metabolites were obeserved as conjugated DBC-11,12-diol, conjugated DBC tetrols, and unconjugated DBC tetrols. The PBPK model was able to predict the time course concentrations of DBC, DBC-11,12-diol, and other DBC metabolites in blood and urine of human volunteers and mice with reasonable accuracy. Agreement between model simulations and measured pharmacokinetic data in mice and human studies demonstrate the success and versatility of our model for interspecies extrapolation and applicability for different doses. Furthermore, our simulations show that internal dose metrics used for risk assessment do not necessarily scale allometrically, and that PBPK modeling provides a reliable approach to appropriately account for interspecies differences in metabolism and physiology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Evaluating Retention Index Score Assumptions to Refine GC–MS Metabolite Identification

As metabolomics grows into a high-throughput and high demand research field, current metrics for the identification of small molecules in gas chromatography–mass spectrometry (GC–MS) still require manual verification. Though steps have been taken to improve scoring metrics by combining spectral similarity (SS) and retention index (RI), the problem persists. A large body of literature has analyzed and refined SS scores, but few studies have explicitly studied improvements to RI scores. Here, in this study, we examined whether uninvestigated assumptions of the RI score are valid and propose ways to improve them. Query RIs were matched to library RI with a generous window of ±35 to avoid unintentional removal of valid compound identifications. Each match was manually verified as a true positive (TP), true negative, or unknown. Metabolites with at least 30 TP identifications were included in downstream analyses, resulting in a total of 87 metabolites from samples of varying complexity and type (e.g., amino acid mixtures, human urine, fungal species, and so on.). Our results showed that the RI score assumptions of normality, consistent variance across metabolites, and a mean error centered at 0 are often violated. We demonstrated through a cross-validation analysis that modifying these underlying assumptions according to empirical metabolite-specific distributions improved the TP and negative rankings. Further, we statistically determined the minimum number of samples required to estimate distributional parameters for scoring metrics. Overall, this work proposes a robust statistical pipeline to reduce the time bottleneck of metabolite identification by improving RI scores and thus minimize the effort to complete manual verification.

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

Standardized multi-omics of Earth’s microbiomes reveals microbial and metabolite diversity

Despite advances in sequencing, lack of standardization makes comparisons across studies challenging and hampers insights into the structure and function of microbial communities across multiple habitats on a planetary scale. Here we present a multi-omics analysis of a diverse set of 880 microbial community samples collected for the Earth Microbiome Project. We include amplicon (16S, 18S, ITS) and shotgun metagenomic sequence data, and untargeted metabolomics data (liquid chromatography-tandem mass spectrometry and gas chromatography mass spectrometry). We used standardized protocols and analytical methods to characterize microbial communities, focusing on relationships and co-occurrences of microbially related metabolites and microbial taxa across environments, thus allowing us to explore diversity at extraordinary scale. In addition to a reference database for metagenomic and metabolomic data, we provide a framework for incorporating additional studies, enabling the expansion of existing knowledge in the form of an evolving community resource. We demonstrate the utility of this database by testing the hypothesis that every microbe and metabolite is everywhere but the environment selects. Our results show that metabolite diversity exhibits turnover and nestedness related to both microbial communities and the environment, whereas the relative abundances of microbially related metabolites vary and co-occur with specific microbial consortia in a habitat-specific manner. We additionally show the power of certain chemistry, in particular terpenoids, in distinguishing Earth’s environments (for example, terrestrial plant surfaces and soils, freshwater and marine animal stool), as well as that of certain microbes including Conexibacter woesei (terrestrial soils), Haloquadratum walsbyi (marine deposits) and Pantoea dispersa (terrestrial plant detritus). This Resource provides insight into the taxa and metabolites within microbial communities from diverse habitats across Earth, informing both microbial and chemical ecology, and provides a foundation and methods for multi-omics microbiome studies of hosts and the environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Microbial secondary metabolites: advancements to accelerate discovery towards application

Microbial secondary metabolites not only have key roles in microbial processes and relationships but are also valued in various sectors of today’s economy, especially in human health and agriculture. The advent of genome sequencing has revealed a previously untapped reservoir of biosynthetic capacity for secondary metabolites indicating that there are new biochemistries, roles and applications of these molecules to be discovered. New predictive tools for biosynthetic gene clusters (BGCs) and their associated pathways have provided insights into this new diversity. Advanced molecular and synthetic biology tools and workflows including cell-based and cell-free expression facilitate the study of previously uncharacterized BGCs, accelerating the discovery of new metabolites and broadening our understanding of biosynthetic enzymology and the regulation of BGCs. These are complemented by new developments in metabolite detection and identification technologies, all of which are important for unlocking new chemistries that are encoded by BGCs. This renaissance of secondary metabolite research and development is catalysing toolbox development to power the bioeconomy.

Dinglasan, Jaime Lorenzo N↗
DOE OSTI2020

Redox cycling-based detection of phenazine metabolites secreted from Pseudomonas aeruginosa in nanopore electrode arrays

The opportunistic pathogen Pseudomonas aeruginosa (P. aeruginosa) produces several redox-active phenazine metabolites, including pyocyanin (PYO) and phenazine-1-carboxamide (PCN), which are electron carrier molecules that also aid in virulence. In particular, PYO is an exclusive metabolite produced by P. aeruginosa, which acts as a virulence factor in hospital-acquired infections and is therefore a good biomarker for identifying early stage colonization by this pathogen. Here, we describe the use of nanopore electrode arrays (NEAs) exhibiting metal–insulator–metal ring electrode architectures for enhanced detection of these phenazine metabolites. The size of the nanopores allows phenazine metabolites to freely diffuse into the interior and access the working electrodes, while the bacteria are excluded. Consequently, highly efficient redox cycling reactions in the NEAs can be accessed by free diffusion unhindered by the presence of bacteria. This strategy yields low limits of detection, i.e. 10.5 and 20.7 nM for PYO and PCN, respectively, values far below single molecule pore occupancy, e.g. at 10.5 nM < n pore > ~ 0.082 per nanopore – a limit which reflects the extraordinary signal amplification in the NEAs. Furthermore, experiments that compared results from minimal medium and rich medium show that P. aeruginosa produces the same types of phenazine metabolites even though growth rates and phenazine production patterns differ in these two media. Here, the NEA measurement strategy developed here should be useful as a diagnostic for pathogens generally and for understanding metabolism in clinically important microbial communities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Nutrient and moisture limitations reveal keystone metabolites linking rhizosphere metabolomes and microbiomes

Plants release a wealth of metabolites into the rhizosphere that can shape the composition and activity of microbial communities in response to environmental stress. The connection between rhizodeposition and rhizosphere microbiome succession has been suggested, particularly under environmental stress conditions, yet definitive evidence is scarce. In this study, we investigated the relationship between rhizosphere chemistry, microbiome dynamics, and abiotic stress in the bioenergy crop switchgrass grown in a marginal soil under nutrient-limited, moisture-limited, and nitrogen (N)-replete, phosphorus (P)-replete, and NP-replete conditions. We combined 16S rRNA amplicon sequencing and LC-MS/MS-based metabolomics to link rhizosphere microbial communities and metabolites. We identified significant changes in rhizosphere metabolite profiles in response to abiotic stress and linked them to changes in microbial communities using network analysis. N-limitation amplified the abundance of aromatic acids, pentoses, and their derivatives in the rhizosphere, and their enhanced availability was linked to the abundance of bacterial lineages from Acidobacteria, Verrucomicrobia, Planctomycetes, and Alphaproteobacteria. Conversely, N-amended conditions increased the availability of N-rich rhizosphere compounds, which coincided with proliferation of Actinobacteria. Treatments with contrasting N availability differed greatly in the abundance of potential keystone metabolites; serotonin and ectoine were particularly abundant in N-replete soils, while chlorogenic, cinnamic, and glucuronic acids were enriched in N-limited soils. Serotonin, the keystone metabolite we identified with the largest number of links to microbial taxa, significantly affected root architecture and growth of rhizosphere microorganisms, highlighting its potential to shape microbial community and mediate rhizosphere plant–microbe interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Transcript and metabolite network perturbations in lignin biosynthetic mutants of Arabidopsis

Abstract Lignin, one of the most abundant polymers in plants, is derived from the phenylpropanoid pathway, which also gives rise to an array of metabolites that are essential for plant fitness. Genetic engineering of lignification can cause drastic changes in transcription and metabolite accumulation with or without an accompanying development phenotype. To understand the impact of lignin perturbation, we analyzed transcriptome and metabolite data from the rapidly lignifying stem tissue in 13 selected phenylpropanoid mutants and wild-type Arabidopsis (Arabidopsis thaliana). Our dataset contains 20,974 expressed genes, of which over 26% had altered transcript levels in at least one mutant, and 18 targeted metabolites, all of which displayed altered accumulation in at least one mutant. We found that lignin biosynthesis and phenylalanine supply via the shikimate pathway are tightly co-regulated at the transcriptional level. The hierarchical clustering analysis of differentially expressed genes (DEGs) grouped the 13 mutants into 5 subgroups with similar profiles of mis-regulated genes. Functional analysis of the DEGs in these mutants and correlation between gene expression and metabolite accumulation revealed system-wide effects on transcripts involved in multiple biological processes.

Plant Sciences↗
DOE OSTI2024

Phytohormones in a universe of regulatory metabolites: lessons from jasmonate

Small-molecule phytohormones exert control over plant growth, development, and stress responses by coordinating the patterns of gene expression within and between cells. Increasing evidence indicates that currently recognized plant hormones are part of a larger group of regulatory metabolites that have acquired signaling properties during the evolution of land plants. This rich assortment of chemical signals reflects the tremendous diversity of plant secondary metabolism, which offers evolutionary solutions to the daunting challenges of sessility and other unique aspects of plant biology. A major gap in our current understanding of plant regulatory metabolites is the lack of insight into the direct targets of these compounds. Here, we illustrate the blurred distinction between classical phytohormones and other bioactive metabolites by highlighting the major scientific advances that transformed the view of jasmonate from an interesting floral scent to a potent transcriptional regulator. Lessons from jasmonate research generally apply to other phytohormones and thus may help provide a broad understanding of regulatory metabolite–protein interactions. In providing a framework that links small-molecule diversity to transcriptional plasticity, we hope to stimulate future research to explore the evolution, functions, and mechanisms of perception of a broad range of plant regulatory metabolites.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Transcripts and genomic intervals associated with variation in metabolite abundance in maize leaves under field conditions

Abstract Plants exhibit extensive environment-dependent intraspecific metabolic variation, which likely plays a role in determining variation in whole plant phenotypes. However, much of the work seeking to use natural variation to link genes and transcript’s impacts on plant metabolism has employed data from controlled environments. Here, we generated and analyzed data on the variation in the abundance of 26 metabolites across 660 maize inbred lines under field conditions. We employ these data and previously published transcript and whole plant phenotype data reported for the same field experiment to identify both genomic intervals (through genome-wide association studies (GWAS)) and transcripts (using both transcriptome-wide association studies (TWAS) and an explainable artificial intelligence (AI) approach based on random forest (RF)) associated with variation in metabolite abundance. Both genome-wide association and random forest-based methods identified substantial numbers of significant associations including genes with plausible links to the metabolites they are associated with. In contrast, the transcriptome-wide association identified only six significant associations. In three cases, genetic markers associated with metabolic variation in our study colocalized with markers linked to variation in non-metabolic traits scored in the same experiment. We speculate that the poor performance of transcriptome-wide association studies in identifying transcript-metabolite associations may reflect a high prevalence of non-linear interactions between transcripts and metabolites and/or a bias towards rare transcripts playing a large role in determining intraspecific metabolic variation.

Mathivanan, Ramesh Kanna↗
DOE OSTI2024

Accelerating the identification of novel secondary metabolites in bioenergy plant root exudates using MicroED

Small molecule metabolites drive inter- and intraspecies communication and dependencies in diverse biological systems, yet a large proportion of these important chemical compounds remain uncharacterized in plants and microbes. Approximately 90% of the metabolites in root exudate profiles are unknown compounds, despite the importance of root exudate composition in plant-microbe interactions. We need advanced analytical capabilities that will support rapid discovery and structural elucidation of metabolites from biological samples that may be limited in quantity and high in complexity. To fill this gap, this project aimed to develop an integrated workflow involving metabolite extraction, separation, and crystallization from plant root exudates followed by characterization using nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry, and microcrystal electron diffraction (MicroED). Using crude root exudates from sorghum, this project successfully developed higher throughput exudate fractionation strategies to obtain pure compounds for crystallization and identified crystals in multiple fractions that diffracted. Additional efforts to increase the throughput of high-quality crystal generation for MicroED, such as crystallization screening and crystallization chaperone exploration, will be needed to further advance root exudate metabolite identification. The overall optimized sample preparation process can then be integrated with the existing data collection and data analysis pipelines for MicroED at PNNL to facilitate more rapid natural product discovery.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Untargeted GC-MS Metabolic Profiling of Anaerobic Gut Fungi Reveals Putative Terpenoids and Strain-Specific Metabolites

Background/Objectives: Anaerobic gut fungi (Neocallimastigomycota) are biotechnologically relevant, lignocellulose-degrading microbes with under-explored biosynthetic potential for secondary metabolites. Untargeted metabolomic profiling with gas chromatography–mass spectrometry (GC-MS) was applied to two gut fungal strains, Anaeromyces robustus and Caecomyces churrovis, to establish a foundational metabolomic dataset to identify metabolites and provide insights into gut fungal metabolic capabilities. Methods: Gut fungi were cultured anaerobically in rumen-fluid-based media with a soluble substrate (cellobiose), and metabolites were extracted using the Metabolite, Protein, and Lipid Extraction (MPLEx) method, enabling metabolomic and proteomic analysis from the same cell samples. Samples were derivatized and analyzed via GC-MS, followed by compound identification by spectral matching to reference databases, molecular networking, and statistical analyses. Results: Distinct metabolites were identified between A. robustus and C. churrovis, including 2,3-dihydroxyisovaleric acid produced by A. robustus and maltotriitol, maltotriose, and melibiose produced by C. churrovis. C. churrovis may polymerize maltotriose to form an extracellular polysaccharide, like pullulan. GC-MS profiling potentially captured sufficiently volatile products of proteomically detected, putative non-ribosomal peptide synthetases and polyketide synthases of A. robustus and C. churrovis. The triterpene squalene and triterpenoid tetrahymanol were putatively identified in A. robustus and C. churrovis. Their conserved, predicted biosynthetic genes—squalene synthase and squalene tetrahymanol cyclase—were identified in A. robustus, C. churrovis, and other anaerobic gut fungal genera. Conclusions: This study provides a foundational, untargeted metabolomic dataset to unmask gut fungal metabolic pathways and biosynthetic potential and to prioritize future efforts for compound isolation and identification.

Biochemistry & Molecular Biology↗