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DOE OSTI2023

Interrogating the role of the milk microbiome in mastitis in the multi-omics era

There is growing interest in a functional understanding of milk-associated microbiota as there is ample evidence that host-associated microbial communities play an active role in host health and phenotype. Mastitis, characterized by painful inflammation of the mammary gland, is prevalent among lactating humans and agricultural animals and is associated with significant clinical and economic consequences. The etiology of mastitis is complex and polymicrobial and correlative studies have indicated alterations in milk microbial community composition. Recent evidence is beginning to suggest that a causal relationship may exist between the milk microbiota and host phenotype in mastitis. Multi-omic approaches can be leveraged to gain a mechanistic, molecular level understanding of how the milk microbiome might modulate host physiology, thereby informing strategies to prevent and ameliorate mastitis. In this paper, we review existing studies that have utilized omics approaches to investigate the role of the milk microbiome in mastitis. We also summarize the strengths and challenges associated with the different omics techniques including metagenomics, metatranscriptomics, metaproteomics, metabolomics and lipidomics and provide perspective on the integration of multiple omics technologies for a better functional understanding of the milk microbiome.

metabolomics↗

DOE OSTI2024

Coupling Metabolic Source Isotopic Pair Labeling and Genome Wide Association for Metabolite and Gene Annotation in Plants (Final Technical Report)

In this project, we applied our labeling pipeline to Arabidopsis and sorghum by feeding tissues with isotopically labeled versions of commercially available amino acids to identify all metabolite features that incorporate the label. In sorghum, we fed five accessions, sampled across the diversity of sorghum, to identify the precursor-of-origin for metabolites that vary between accessions as well as those that may be missing from a single reference genotype. This provided us with precursor-of-origin annotation for thousands of unknown metabolites. We then used GWA to map genes responsible for the synthesis of precursor-of-origin classified metabolites. For sorghum leaf and root ducible metabolites, we performed untargeted metabolomics on leaf and root tissues from 300 diverse genotyped sorghum inbred lines. The amino acid precursor-of-origin metabolite library were then used to identify the corresponding metabolites in the GWA data sets and to identify novel gene-metabolite associations. Finally, we utilized existing and newly generated sequenced EMS mutants of sorghum to validate the predicted gene-metabolite relationships that our labelling analysis identified. In parallel, we conducted similar feeding experiments in Arabidopsis to categorize metabolites based on precursor-of-origin, identify those that vary across our existing Arabidopsis metabolite GWA dataset, and identify genes required for the synthesis of each metabolite. To provide an independent test of gene annotation and pathway involvement, we tested the GWA gene-metabolite associations in Arabidopsis by analyzing the metabolic phenotypes of gene knockouts. Genes of particular interest from both sorghum and Arabidopsis were studied in detail by directly measuring the activity of the corresponding enzymes following heterologous expression. In summary, this work classified as-yet-unknown amino acid-derived metabolites and identified genes involved in their production generated through “omics” technologies. This information was used to validate gene function and identify new metabolism in Arabidopsis and sorghum.

09 BIOMASS FUELS↗

DOE OSTI2022

mTOR regulates aerobic glycolysis through NEAT1 and nuclear paraspeckle-mediated mechanism in hepatocellular carcinoma

Hepatocellular Carcinoma (HCC) is a major form of liver cancer and a leading cause of cancer-related death worldwide. New insights into HCC pathobiology and mechanism of drug actions are urgently needed to improve patient outcomes. HCC undergoes metabolic reprogramming of glucose metabolism from respiration to aerobic glycolysis, a phenomenon known as the ‘Warburg Effect’ that supports rapid cancer cell growth, survival, and invasion. mTOR is known to promote Warburg Effect, but the underlying mechanism(s) remains poorly defined. The aim of this study is to understand the mechanism(s) and significance of mTOR regulation of aerobic glycolysis in HCC. We profiled mTORC1-dependent long non-coding RNAs (lncRNAs) by RNA-seq of HCC cells treated with rapamycin. Chromatin immunoprecipitation (ChIP) and luciferase reporter assays were used to explore the transcriptional regulation of NEAT1 by mTORC1. [U- 13 C]-glucose labeling and metabolomic analysis, extracellular acidification Rate (ECAR) by Seahorse XF Analyzer, and glucose uptake assay were used to investigate the role of mTOR-NEAT1-NONO signaling in the regulation of aerobic glycolysis. RNA immunoprecipitation (RIP) and NONO-binding motif scanning were performed to identify the regulatory mechanism of pre-mRNA splicing by mTOR-NEAT1. Myristoylated AKT1 (mAKT1)/NRASV 12 -driven HCC model developed by hydrodynamic transfection (HDT) was employed to explore the significance of mTOR-NEAT1 signaling in HCC tumorigenesis and mTOR-targeted therapy. mTOR regulates lncRNA transcriptome in HCC and that NEAT1 is a major mTOR transcriptional target. Interestingly, although both NEAT1_1 and NEAT1_2 are down-regulated in HCC, only NEAT1_2 is significantly correlated with poor overall survival of HCC patients. NEAT1_2 is the organizer of nuclear paraspeckles that sequester the RNA-binding proteins NONO and SFPQ. We show that upon oncogenic activation, mTORC1 suppresses NEAT1_2 expression and paraspeckle biogenesis, liberating NONO/SFPQ, which in turn, binds to U5 within the spliceosome, stimulating mRNA splicing and expression of key glycolytic enzymes. This series of actions lead to enhanced glucose transport, aerobic glycolytic flux, lactate production, and HCC growth both in vitro and in vivo. Furthermore, the paraspeckle-mediated mechanism is important for the anticancer action of US FDA-approved drugs rapamycin/temsirolimus. These findings reveal a molecular mechanism by which mTOR promotes the ‘Warburg Effect’, which is important for the metabolism and development of HCC, and anticancer response of mTOR-targeted therapy.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Data for Metabolic Engineering of Low-pH-Tolerant Non-Model Yeast, Issatchenkia orientalis , for Production of Citramalate

Methyl methacrylate (MMA) is an important petrochemical with many applications. However, its manufacture has a large environmental footprint. Combined biological and chemical synthesis (semisynthesis) may be a promising alternative to reduce both cost and environmental impact, but strains that can produce the MMA precursor (citramalate) at low pH are required. A non-conventional yeast, Issatchenkia orientalis , may prove ideal, as it can survive extremely low pH. Here, we demonstrate the engineering of I. orientalis for citramalate production. Using sequence similarity network analysis and subsequent DNA synthesis, we selected a more active citramalate synthase gene (cimA) variant for expression in I. orientalis . We then adapted a piggyBac transposon system for I. orientalis that allowed us to simultaneously explore the effects of different cimA gene copy numbers and integration locations. A batch fermentation showed the genome-integrated-cimA strains produced 2.0 g/L citramalate in 48 h and a yield of up to 7% mol citramalate/mol consumed glucose. These results demonstrate the potential of I. orientalis as a chassis for citramalate production.

Conversion↗

DOE OSTI2024

Gut microbiota carbon and sulfur metabolisms support Salmonella infections

Abstract Salmonella enterica serovar Typhimurium is a pervasive enteric pathogen and ongoing global threat to public health. Ecological studies in the Salmonella impacted gut remain underrepresented in the literature, discounting microbiome mediated interactions that may inform Salmonella physiology during colonization and infection. To understand the microbial ecology of Salmonella remodeling of the gut microbiome, we performed multi-omics on fecal microbial communities from untreated and Salmonella-infected mice. Reconstructed genomes recruited metatranscriptomic and metabolomic data providing a strain-resolved view of the expressed metabolisms of the microbiome during Salmonella infection. These data informed possible Salmonella interactions with members of the gut microbiome that were previously uncharacterized. Salmonella-induced inflammation significantly reduced the diversity of genomes that recruited transcripts in the gut microbiome, yet increased transcript mapping was observed for seven members, among which Luxibacter and Ligilactobacillus transcript read recruitment was most prevalent. Metatranscriptomic insights from Salmonella and other persistent taxa in the inflamed microbiome further expounded the necessity for oxidative tolerance mechanisms to endure the host inflammatory responses to infection. In the inflamed gut lactate was a key metabolite, with microbiota production and consumption reported amongst members with detected transcript recruitment. We also showed that organic sulfur sources could be converted by gut microbiota to yield inorganic sulfur pools that become oxidized in the inflamed gut, resulting in thiosulfate and tetrathionate that support Salmonella respiration. This research advances physiological microbiome insights beyond prior amplicon-based approaches, with the transcriptionally active organismal and metabolic pathways outlined here offering intriguing intervention targets in the Salmonella-infected intestine.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

In Vivo Thermodynamic Analysis of Glycolysis in Clostridium thermocellum and Thermoanaerobacterium saccharolyticum Using 13 C and 2 H Tracers

Clostridium thermocellum and Thermoanaerobacterium saccharolyticum are thermophilic anaerobic bacteria with complementary metabolic capabilities that utilize distinct glycolytic pathways for the conversion of cellulosic sugars to biofuels. We integrated quantitative metabolomics with 2 H and 13 C metabolic flux analysis to investigate the in vivo reversibility and thermodynamics of the central metabolic networks of these two microbes. We found that the glycolytic pathway in C. thermocellum operates remarkably close to thermodynamic equilibrium, with an overall drop in Gibbs free energy 5-fold lower than that of T. saccharolyticum or anaerobically grown Escherichia coli . The limited thermodynamic driving force of glycolysis in C. thermocellum could be attributed in large part to the small free energy of the phosphofructokinase reaction producing fructose bisphosphate. The ethanol fermentation pathway was also substantially more reversible in C. thermocellummthan in T. saccharolyticum. These observations help explain the comparatively low ethanol titers of C. thermocellum and suggest engineering interventions that can be used to increase its ethanol productivity and glycolytic rate. In addition to thermodynamic analysis, we used our isotope tracer data to reconstruct the T. saccharolyticum central metabolic network, revealing exclusive use of the Embden-Meyerhof-Parnas (EMP) pathway for glycolysis, a bifurcated tricarboxylic acid (TCA) cycle, and a sedoheptulose bisphosphate bypass active within the pentose phosphate pathway. Thermodynamics constitutes a key determinant of flux and enzyme efficiency in metabolic networks. Here, we provide new insights into the divergent thermodynamics of the glycolytic pathways of C. thermocellum and T. saccharolyticum, two industrially relevant thermophilic bacteria whose metabolism still is not well understood. We report that while the glycolytic pathway in T. saccharolyticum is as thermodynamically favorable as that found in model organisms, such as E. coli or Saccharomyces cerevisiae , the glycolytic pathway of C. thermocellum operates near equilibrium. The use of a near-equilibrium glycolytic pathway, with potentially increased ATP yield, by this cellulolytic microbe may represent an evolutionary adaptation to growth on cellulose, but it has the drawback of being highly susceptible to product feedback inhibition. The results of this study will facilitate future engineering of high-performance strains capable of transforming cellulosic biomass to biofuels at high yields and titers.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Influence of Mild Chronic Stress and Social Isolation on Acute Ozone-Induced Alterations in Stress Biomarkers and Brain-Region-Specific Gene Expression in Male Wistar–Kyoto Rats

Individuals with psychosocial stress often experience an exaggerated response to air pollutants. Ozone (O 3 ) exposure has been associated with the activation of the neuroendocrine stress-response system. We hypothesized that preexistent mild chronic stress plus social isolation (CS), or social isolation (SI) alone, would exacerbate the acute effects of O 3 exposure on the circulating adrenal-derived stress hormones, and the expression of the genes regulating glucocorticoid stress signaling via an altered stress adaptation in a brain-region-specific manner. Male Wistar–Kyoto rats (5 weeks old) were socially isolated, plus were subjected to either CS (noise, confinement, fear, uncomfortable living, hectic activity, and single housing), SI (single housing only, restricted handling and no enrichment) or no stress (NS; double housing, frequent handling and enrichment provided) for 8 weeks. The rats were then exposed to either air or O 3 (0.8 ppm for 4 h), and the samples were collected immediately after. The indicators of sympathetic and hypothalamic–pituitary axis (HPA) activation (i.e., epinephrine, corticosterone, and lymphopenia) increased with O 3 exposure, but there were no effects from CS or SI, except for the depletion of serum BDNF. CS and SI revealed small changes in brain-region-specific glucocorticoid-signaling-associated markers of gene expression in the air-exposed rats (hypothalamic Nr3c1, Nr3c2 Hsp90aa1, Hspa4 and Cnr1 inhibition in SI; hippocampal HSP90aa1 increase in SI; and inhibition of the bed nucleus of the stria terminalis (BNST) Cnr1 in CS). Gene expression across all brain regions was altered by O 3 , reflective of glucocorticoid signaling effects, such as Fkbp5 in NS, CS and SI. The SI effects on Fkbp5 were greatest for SI in BNST. O 3 increased Cnr2 expression in the hypothalamus and olfactory bulbs of the NS and SI groups. O 3 , in all stress conditions, generally inhibited the expression of Nr3c1 in all brain regions, Nr3c2 in the hippocampus and hypothalamus and Bdnf in the hippocampus. SI, in general, showed slightly greater O 3 -induced changes when compared to NS and CS. Serum metabolomics revealed increased sphingomyelins in the air-exposed SI and O 3 -exposed NS, with underlying SI dampening some of the O 3 -induced changes. These results suggest a potential link between preexistent SI and acute O 3 -induced increases in the circulating adrenal-derived stress hormones and brain-region-specific gene expression changes in glucocorticoid signaling, which may partly underlie the stress dynamic in those with long-term SI.

gene expression↗

DOE OSTI2025

Root exudate lipids: Uncovering chemodiversity and carbon stability potential

Root-derived carbon has been shown to contribute more to soil carbon stocks than aboveground litter. Yet the molecular chemodiversity of root exudates remains poorly understood due to limited characterization and annotation. In this study, we characterized the molecular chemodiversity and production of metabolites and lipids in root exudates from field grown mature tall wheatgrass (Thinopyrum ponticum). We discovered a diversity of lipids, including substantial levels of triacylglycerols (∼19 μg/g fresh root per min), fatty acyls, sphingolipids, sterol lipids, and glycerophospholipids, some of which have not been previously documented in root exudates. By integrating tandem mass spectral library searching and deep learning-based chemical class assignment, our metabo-lipidomics approach significantly expanded the known molecular diversity of root exudates. Rates of lipid derived carbon production were approximately double that of polar metabolites (lipids: 81.52 ± 13.81 vs polar metabolites: 38.41 ± 5.93 μg C g −1 fresh root mass min −1 ) with an order of magnitude higher carbon to nitrogen ratios (lipids: 459 ± 90 vs polar metabolites: 14.40 ± 0.58). Exudate lipids displayed highly negative nominal oxidation state of carbon (−1.182 to −1.909), indicating that these compounds may be less favorable for microbial decomposition. Together our results suggest the potential of root exudate lipids to contribute to stable carbon pools in soil, supporting long-term carbon storage. This work advances understanding of plant-derived lipid inputs to soil and underscores the need for future studies on the functional roles of lipids in shaping root-microbe-soil interactions, microbial activity, soil structure, and nutrient availability – contributing to soil health.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Advances in mass spectrometry-enabled multiomics at single-cell resolution

We report biological organisms are multifaceted, intricate systems where slight perturbations can result in extensive changes in gene expression, protein abundance and/or activity, and metabolic flux. These changes occur at different timescales, spatially across cells of heterogeneous origins, and within single-cells. Hence, multimodal measurements at the smallest biological scales are necessary to capture dynamic changes in heterogeneous biological systems. Of the analytical techniques used to measure biomolecules, mass spectrometry (MS) has proven to be a powerful option due to its sensitivity, robustness, and flexibility with regard to the breadth of biomolecules that can be analyzed. Recently, many studies have coupled MS to other analytical techniques with the goal of measuring multiple modalities from the same single-cell. It is with these concepts in mind that we focus this review on MS-enabled multiomic measurements at single-cell or near-single- cell resolution.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Respiration data, microbial community assembly data, and FTICR-MS data associated with: “Disturbance Triggers Non-Linear Microbe-Environment Feedbacks. Sengupta et al., 2021, Biogeosciences”

This data package is associated with the manuscript “Disturbance Triggers Non-Linear Microbe-Environment Feedbacks, in revision in Biogeosciences (Sengupta et al. and 2021;https://bg.copernicus.org/preprints/bg-2021-51/). The study used hyporheic zone sediments as a model system to provide an integrated view of how disturbance modulates linkages among microbial ecology, biogeochemistry, and organic matter thermodynamics. Laboratory experiments exposed hyporheic sediment to varying wetting/drying dynamics. Data types include dissolved oxygen rates used to derive respiration rates, Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) data used to derive thermodynamic properties of organic matter, and microbial community assembly metrics derived from amplicon-sequence data of putatively active (cDNA) and whole community (gDNA). The outcomes of the study are condensed into a broadly applicable conceptual model linking external forcing, internal dynamics, and history. This data package is comprised of a file-level metadata (FLMD) csv, metadata csv, and seven folders that contain csv files, R scripts, xml files, and associated documentation: (1) Rates, (2) bNTI, and (3) FTICR, (4) Statistics_Analyses, (5) Raw OTU Beta dispersion Analysis, (6) bMNTD Randomizations, and (7) Data Dictionaries. The FLMD file has a description of each file included in the data package.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Inferring the Contribution of Microbial Taxa and Organic Matter Molecular Formulas to Ecological Assembly

Understanding the mechanisms underlying the assembly of communities has long been the goal of many ecological studies. While several studies have evaluated community wide ecological assembly, fewer have focused on investigating the impacts of individual members within a community or assemblage on ecological assembly. Here, we adapted a previous null model β-nearest taxon index (βNTI) to measure the contribution of individual features within an ecological community to overall assembly. This new metric, called feature-level βNTI (βNTI feat ), enables researchers to determine whether ecological features (e.g., individual microbial taxa) contribute to divergence, convergence, or have insignificant impacts across spatiotemporally resolved metacommunities or meta-assemblages. Using βNTI feat , we revealed that unclassified microbial lineages often contributed to community divergence while diverse groups (e.g., Crenarchaeota, Alphaproteobacteria, and Gammaproteobacteria) contributed to convergence. We also demonstrate that βNTI feat can be extended to other ecological assemblages such as organic molecules comprising organic matter (OM) pools. OM had more inconsistent trends compared to the microbial community though CHO-containing molecular formulas often contributed to convergence, while nitrogen and phosphorus-containing formulas contributed to both convergence and divergence. A network analysis was used to relate βNTI feat values from the putatively active microbial community and the OM assemblage and examine potentially common contributions to ecological assembly across different communities/assemblages. This analysis revealed that P-containing formulas often contributed to convergence/divergence separately from other ecological features and N-containing formulas often contributed to assembly in coordination with microorganisms. Additionally, members of Family Geobacteraceae were often observed to contribute to convergence/divergence in conjunction with both N- and P-containing formulas, suggesting a coordinated ecological role for family members and the nitrogen/phosphorus cycle. Overall, we show that βNTI feat offers opportunities to investigate the community or assemblage members, which shape the phylogenetic or functional landscape, and demonstrate the potential to evaluate potential points of coordination across various community types.

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 OSTI2020

Switchgrass Rhizosphere Metabolite Chemistry Driven by Nitrogen Availability

Plants and soil microorganisms interact closely in the rhizosphere where plants may exchange carbon (C) for functional benefits from the microbial community. For example, the bioenergy crop, switchgrass (Panicum virgatum) is thought to exchange root-exuded C for nitrogen (N) fixed by diazotrophs (free-living N-fixers). However, this interaction is not well characterized and it is not known how or if switchgrass responds to diazotrophs or their activity. To explore this question, we assessed rhizosphere metabolite chemistry of switchgrass grown in a hydroponic system under two N levels and under inoculated or uninoculated conditions. Plants were grown with the inoculum Azotobacter vinelandii DJ for 3 days before harvest. We found switchgrass root exudate chemistry to be driven by N availability. Total metabolite concentrations were generally greater under high N versus low N and unaffected by inoculation. Examination of rhizosphere chemical fingerprints indicates metabolite chemistry was also driven strongly by N availability with a greater relative abundance of carbohydrates under high N and greater relative abundance of organic acids under low N. We also found evidence of changes in rhizosphere chemical fingerprints by inoculation treatment. However, we found little evidence of N treatment and inoculation interaction effects that suggests this response is not directly mediated by N availability.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

The ‘photosynthetic C 1 pathway’ links carbon assimilation and growth in California poplar

Although primarily studied in relation to photorespiration, serine metabolism in chloroplasts may play a key role in plant CO 2 fertilization responses by linking CO 2 assimilation with growth. Here, we show that the phosphorylated serine pathway is part of a 'photosynthetic C 1 pathway' and demonstrate its high activity in foliage of a C 3 tree where it rapidly integrates photosynthesis and C 1 metabolism contributing to new biomass via methyl transfer reactions, imparting a large natural 13 C-depleted signature. Using 13 CO 2 -labelling, we show that leaf serine, the S-methyl group of leaf methionine, pectin methyl esters, and the associated methanol released during cell wall expansion during growth, are directly produced from photosynthetically-linked C 1 metabolism, within minutes of light exposure. We speculate that the photosynthetic C 1 pathway is highly conserved across the photosynthetic tree of life, is responsible for synthesis of the greenhouse gas methane, and may have evolved with oxygenic photosynthesis by providing a mechanism of directly linking carbon and ammonia assimilation with growth. Although the rise in atmospheric CO 2 inhibits major metabolic pathways like photorespiration, our results suggest that the photosynthetic C 1 pathway may accelerate and represents a missing link between enhanced photosynthesis and plant growth rates during CO 2 fertilization under a changing climate.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

Effects of photon irradiation in the presence and absence of hindlimb unloading on the behavioral performance and metabolic pathways in the plasma of Fischer rats

The space environment astronauts experience during space missions consists of multiple environmental challenges, including microgravity. In this study, we assessed the behavioral and cognitive performances of male Fisher rats 2 months after sham irradiation or total body irradiation with photons in the absence or presence of simulated microgravity. We analyzed the plasma collected 9 months after sham irradiation or total body irradiation for distinct alterations in metabolic pathways and to determine whether changes to metabolic measures were associated with specific behavioral and cognitive measures. A total of 344 male Fischer rats were irradiated with photons (6 MeV; 3, 8, or 10 Gy) in the absence or presence of simulated weightlessness achieved using hindlimb unloading (HU). To identify potential plasma biomarkers of photon radiation exposure or the HU condition for behavioral or cognitive performance, we performed regression analyses. The behavioral effects of HU on activity levels in an open field, measures of anxiety in an elevated plus maze, and anhedonia in the M&M consumption test were more pronounced than those of photon irradiation. Phenylalanine, tyrosine, and tryptophan metabolism, and phenylalanine metabolism and biosynthesis showed very strong pathway changes, following photon irradiation and HU in animals irradiated with 3 Gy. Here, 29 out of 101 plasma metabolites were associated with 1 out of 13 behavioral measures. In the absence of HU, 22 metabolites were related to behavioral and cognitive measures. In HU animals that were sham-irradiated or irradiated with 8 Gy, one metabolite was related to behavioral and cognitive measures. In HU animals irradiated with 3 Gy, six metabolites were related to behavioral and cognitive measures. These data suggest that it will be possible to develop stable plasma biomarkers of behavioral and cognitive performance, following environmental challenges like HU and radiation exposure.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

The Power of Many: An Ensemble Approach to Spectral Similarity

Quantifying the similarity between two mass spectra─a known reference mass spectrum and an unidentified sample mass spectrum─is at the heart of compound identification workflows in gas chromatography–mass spectrometry (GC-MS). The reference spectrum most like the sample is assigned as its identification (provided some quantitative similarity threshold is met, e.g., 80%) and thus accurately measuring similarity is essential. Significant research has gone toward developing metrics for this purpose, each of which has attempted to improve upon existing methods by incorporating GC-MS-specific information (e.g., peak ratios or retention times) or adopting various statistical and algorithmic frameworks. While this active development has led to a plethora of similarity metrics with demonstrated value across different contexts, the unfortunate consequence has been confusion surrounding which metric should be used as a global standard. No such metric is currently accepted as the standard method because different metrics have demonstrated optimal performance in different contexts. In this work, we propose an ensemble approach to spectral similarity scoring that combines the collective information from across existing similarity metrics to form an improved, globally representative similarity metric as a step toward establishing a global standard method. In conclusion, the resulting ensemble metrics are evaluated on over 88,000 spectra of varying complexity and demonstrate improved abilities to accurately rank the correct reference spectrum as the top-matching candidate for a sample relative to the rankings generated by individual similarity scores.

Carbohydrates↗

DOE OSTI2024

Bioactive exometabolites drive maintenance competition in simple bacterial communities

During prolonged resource limitation, bacterial cells can persist in metabolically active states of non-growth. These maintenance periods, such as those experienced in stationary phase, can include upregulation of secondary metabolism and release of exometabolites into the local environment. As resource limitation is common in many environmental microbial habitats, we hypothesized that neighboring bacterial populations employ exometabolites to compete or cooperate during maintenance and that these exometabolite-facilitated interactions can drive community outcomes. Here, we evaluated the consequences of exometabolite interactions over the stationary phase among three environmental strains: Burkholderia thailandensis E264, Chromobacterium subtsugae ATCC 31532, and Pseudomonas syringae pv. tomato DC3000. We assembled them into synthetic communities that only permitted chemical interactions. We compared the responses (transcripts) and outputs (exometabolites) of each member with and without neighbors. We found that transcriptional dynamics were changed with different neighbors and that some of these changes were coordinated between members. The dominant competitor B. thailandensis consistently upregulated biosynthetic gene clusters to produce bioactive exometabolites for both exploitative and interference competition. These results demonstrate that competition strategies during maintenance can contribute to community-level outcomes. It also suggests that the traditional concept of defining competitiveness by growth outcomes may be narrow and that maintenance competition could be an additional or alternative measure.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

1H-NMR characterization of soil dissolved organic matter from soil samples in control and warming plots in Blodgett Forest, CA (2014 and 2018)

The pathways of carbon transport and loss through and from soils—soil organic matter (SOM) depolymerization to dissolved organic carbon and mineralization to carbon dioxide (CO2)—are fundamentally driven by microbial activity, which is strongly regulated by environmental conditions. As part of Lawrence Berkeley National Laboratory Terrestrial Ecosystem Science Belowground Biogeochemistry Science Focus Area (SFA), we have established a novel whole-soil long-term warming experiment at the University of California (UC) Blodgett Forest Research Station (Sierra Nevada) in 2014, where we study the role of biogeochemical, microbial and geochemical process interactions in SOM (soil organic matter) decomposition and stabilization. This package contains metabolite data obtained through 1H nuclear magnetic resonance (NMR) spectroscopy on water-extracted soils. Soil samples were collected in 2014/06/03 and 2018/06/04 from 3 replicated paired plots that had been subjected to experimental warming since June 2014 to simulate a predicted climate change scenario for northern California. The following files are included: (1) nmr_h2o_data_raw.csv: raw data, (2) nmr_h2o_data_processed.csv: computed compound concentrations and metadata, (3) nmr_h2o_compound_metadata.csv: compound metadata, (4) nmr_h2o_sample_metadata.csv: sample metadata

1H-NMR (nucleic magnetic resonance) spectroscopy↗