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At least 253 records · Page 14

Multi-Omics Driven Metabolic Network Reconstruction and Analysis of Lignocellulosic Carbon Utilization in Rhodosporidium toruloides

An oleaginous yeast Rhodosporidium toruloides is a promising host for converting lignocellulosic biomass to bioproducts and biofuels. In this work, we performed multi-omics analysis of lignocellulosic carbon utilization in R. toruloides and reconstructed the genome-scale metabolic network of R. toruloides . High-quality metabolic network models for model organisms and orthologous protein mapping were used to build a draft metabolic network reconstruction. The reconstruction was manually curated to build a metabolic model using functional annotation and multi-omics data including transcriptomics, proteomics, metabolomics, and RB-TDNA sequencing. The multi-omics data and metabolic model were used to investigate R. toruloides metabolism including lipid accumulation and lignocellulosic carbon utilization. The developed metabolic model was validated against high-throughput growth phenotyping and gene fitness data, and further refined to resolve the inconsistencies between prediction and data. We believe that this is the most complete and accurate metabolic network model available for R. toruloides to date.

09 BIOMASS FUELS↗

Xanthohumol Alters Gut Microbiota Metabolism and Bile Acid Dynamics in Gastrointestinal Simulation Models of Eubiotic and Dysbiotic States

Xanthohumol (XN), a polyphenol from hops (Humulus lupulus), exhibits antioxidant, anti-inflammatory, antihyperlipidemic, and chemo-preventive activity. Preclinical evidence suggests gut microbiota are critical to mediating some of these bioactivities. Nevertheless, its precise impact on human gut microbiota, particularly at supplemental doses, remains poorly characterized. We evaluated 200 mg/day XN for 3 weeks on human gut microbiota in a eubiotic and dysbiotic model using the Simulator of the Human Intestinal Microbial Ecosystem (SHIME®). Functional assessments of microbiota included quantification of XN metabolites, short-chain fatty acids (SCFAs), and untargeted metabolomics of the digestive metabolome. Bacterial composition was assessed by 16S rRNA gene sequencing. XN reduced alpha-diversity and short-chain fatty acid production in both models, as well as altered taxa abundance variably between models. XN disrupted bile acid metabolism through inhibition of microbial bile salt hydrolase (BSH). The modulation of bile acid metabolism has important implications for host-level bioactivity of XN.

Humulus lupulus↗

Simulating the metabolic pathway dynamics of an organism

Disclosed herein are systems and methods for determining metabolic pathway dynamics using time series multiomics data. In one example, after receiving time series multiomics data comprising time-series metabolomics data associated a metabolic pathway and time-series proteomics data associated with the metabolic pathway, derivatives of the time series multiomics data can be determined. A machine learning model, representing a metabolic pathway dynamics model, can be trained using the time series multiomics data and the derivatives of the time series multiomics data, wherein the metabolic pathway dynamics model relates the time-series metabolomics data and time-series proteomics data to the derivatives of the time series multiomics data. The method can include simulating a virtual strain of the organism using the metabolic pathway dynamics model.

Costello, Zachary↗

Comparability of Liquid Chromatography Tandem Mass Spectrometry Analysis of Dissolved Organic Matter across Laboratories

Non-targeted liquid chromatography tandem highresolution mass spectrometry (LC−MS/MS) is increasingly applied for the structure-resolved chemical analysis of dissolved organic matter (DOM). With new developments in MS instrumentation and analysis software, the approach has gained substantial momentum over the past decade. However, achieving high-quality analytical data that is reproducible and comparable across laboratories can be a bottleneck in non-targeted metabolomics and organic matter chemical analysis, especially for data reuse in repository-scale analyses. Understanding the capabilities as well as challenges of comparing LC−MS/MS data from different laboratories is necessary for inferring global trends from public data sets. To illuminate instrumentation factors that drive differences and variability, we used a standardized data analysis pipeline, including classical (CMN) and featurebased molecular networking (FBMN), to analyze data from a ring trial by 24 laboratories on identical sample sets of algal and DOM extracts that were mixed in predefined concentrations and spiked with standards. Our results showed that data sets from similar mass spectrometer types with unified instrument parameters were qualitatively comparable, resolving the same general trends and shared mass spectral features. Interlaboratory comparability was best for high-intensity features, while low-intensity features showed greater detection variability. Our analysis also highlights challenges when comparing data from instruments with different acquisition rates or operating with less standardized methods. Lastly, we provide recommendations for data integration, public data sharing, standardization, and best practices for standardized LC−MS/MS data acquisition, which will be critical for long-term time series and intercomparability of DOM chemical analyses.

DOM↗

Dynamic nitrogen fixation in an aerobic endophyte of Populus

Biological nitrogen fixation by microbial diazotrophs can contribute significantly to nitrogen availability in non-nodulating plant species. In this study of molecular mechanisms and gene expression relating to biological nitrogen fixation, the aerobic nitrogen-fixing endophyte Burkholderia vietnamiensis, strain WPB, isolated from Populus trichocarpa served as a model for endophyte–poplar interactions. Nitrogen-fixing activity was observed to be dynamic on nitrogen-free medium with a subset of colonies growing to form robust, raised globular like structures. Secondary ion mass spectrometry (NanoSIMS) confirmed that N-fixation was uneven within the population. A fluorescent transcriptional reporter (GFP) revealed that the nitrogenase subunit nifH is not uniformly expressed across genetically identical colonies of WPB and that only ~11% of the population was actively expressing the nifH gene. Higher nifH gene expression was observed in clustered cells through monitoring individual bacterial cells using single-molecule fluorescence in situ hybridization. Through 15 N 2 enrichment, we identified key nitrogenous metabolites and proteins synthesized by WPB and employed targeted metabolomics in active and inactive populations. We cocultivated WPB Pnif-GFP with poplar within a RhizoChip, a synthetic soil habitat, which enabled direct imaging of microbial nifH expression within root epidermal cells. We observed that nifH expression is localized to the root elongation zone where the strain forms a unique physical interaction with the root cells. This work employed comprehensive experimentation to identify novel mechanisms regulating both biological nitrogen fixation and beneficial plant–endophyte interactions.

15 N-tracking metabolomics↗

Expression of dehydroshikimate dehydratase in poplar induces transcriptional and metabolic changes in the phenylpropanoid pathway

Abstract Modification of lignin in feedstocks via genetic engineering aims to reduce biomass recalcitrance to facilitate efficient conversion processes. These improvements can be achieved by expressing exogenous enzymes that interfere with native biosynthetic pathways responsible for the production of the lignin precursors. In planta expression of a bacterial 3-dehydroshikimate dehydratase in poplar trees reduced lignin content and altered the monomer composition, which enabled higher yields of sugars after cell wall polysaccharide hydrolysis. Understanding how plants respond to such genetic modifications at the transcriptional and metabolic levels is needed to facilitate further improvement and field deployment. In this work, we acquired fundamental knowledge on lignin-modified poplar expressing 3-dehydroshikimate dehydratase using RNA-seq and metabolomics. The data clearly demonstrate that changes in gene expression and metabolite abundance can occur in a strict spatiotemporal fashion, revealing tissue-specific responses in the xylem, phloem, or periderm. In the poplar line that exhibited the strongest reduction in lignin, we found that 3% of the transcripts had altered expression levels and ~19% of the detected metabolites had differential abundance in the xylem from older stems. The changes affected predominantly the shikimate and phenylpropanoid pathways as well as secondary cell wall metabolism, and resulted in significant accumulation of hydroxybenzoates derived from protocatechuate and salicylate.

59 BASIC BIOLOGICAL SCIENCES↗

The Natural Products Magnetic Resonance Database (NP-MRD) for 2025

The Natural Products Magnetic Resonance Database or NP-MRD (https://np-mrd.org) is a comprehensive, freely accessible, web-based resource for the deposition, distribution, extraction and retrieval of nuclear magnetic resonance (NMR) data on natural products. The NP-MRD was initially established to support compound de-replication and data dissemination for the natural products community. However, that community has now grown to include many users from the metabolomics, microbiomics, foodomics and nutrition science fields. Indeed, since its launch in 2021, the NP-MRD has expanded enormously in size, scope and popularity. The current version of NP-MRD now contains nearly 7X more compounds (281,859 vs. 40,908) and 7X more NMR spectra (5.1 million vs. 817,000) than the first release. More specifically, an additional 4.6 million predicted spectra and another 11,000 spectra simulated from experimental chemical shifts were deposited into the database. Likewise, the number of NMR raw spectral data depositions has grown from a 165 spectra per year to more than 10,000 per year. As a result of this expansion, the number of monthly webpage views has grown from 55 to 20,000 and the number of monthly visitors has increased from 7 to 2500. To address this growth and to better support the expanding needs of its diverse community of users, many additional improvements to the NP-MRD have been made. These include significant enhancements to the data submission process, important improvements to the visualization and display of NMR spectra, notable updates to the database’s spectral search utilities and useful additions to support better NMR spectral analysis/prediction. Significant efforts have also been undertaken to remediate and update many of NP-MRD’s database entries. This manuscript describes these database improvements and expansion efforts, along with how they have been implemented and what future upgrades to the NP-MRD are planned.

Artifical Intelligence↗

Computational tools and algorithms for ion mobility spectrometry-mass spectrometry

Ion mobility spectrometry-mass spectrometry (IMS-MS or IM-MS) is a powerful analytical technique that combines the gas-phase separation capabilities of IM with the identification and quantification capabilities of MS. IM-MS can differentiate molecules with indistinguishable masses but different structures (e.g., isomers, isobars, molecular classes, and contaminant ions). The importance of this analytical technique is reflected by a staged increase in the number of applications for molecular characterization across a variety of fields, from different MS-based omics (proteomics, metabolomics, lipidomics, etc.) to the structural characterization of glycans, organic matter, proteins, and macromolecular complexes. With the increasing application of IM-MS there is a pressing need for effective and accessible computational tools. This article presents an overview of the most recent free and open-source software tools specifically tailored for the analysis and interpretation of data derived from IM-MS instrumentation. This review enumerates these tools and outlines their main algorithmic approaches, while highlighting representative applications across different fields. Finally, a discussion of current limitations and expectable improvements is presented.

59 BASIC BIOLOGICAL SCIENCES↗

Discovery of treatment for nerve agents targeting a new metabolic pathway

The inhibition of acetylcholinesterase is regarded as the primary toxic mechanism of action for chemical warfare agents. Recently, there have been numerous reports suggesting that metabolic processes could significantly contribute to toxicity. As such, we applied a multi-omics pipeline to generate a detailed cascade of molecular events temporally occurring in guinea pigs exposed to VX. Proteomic and metabolomic profiling resulted in the identification of several enzymes and metabolic precursors involved in glycolysis and the TCA cycle. All lines of experimental evidence indicated that there was a blockade of the TCA cycle at isocitrate dehydrogenase 2, which converts isocitrate to α-ketoglutarate. Using a primary beating cardiomyocyte cell model, we were able to determine that the supplementation of α-ketoglutarate subsequently rescued cells from the acute effects of VX poisoning. This study highlights the broad impacts that VX has and how understanding these mechanisms could result in new therapeutics such as α-ketoglutarate.

59 BASIC BIOLOGICAL SCIENCES↗

Investigating the role of the transcriptional regulator Ure2 on the metabolism of Saccharomyces cerevisiae: a multi-omics approach

Ure2 regulates nitrogen catabolite repression in Saccharomyces cerevisiae. Deletion of URE2 induces a physiological state mimicking the nitrogen starvation and autophagic responses. Previous work has shown that deletion of URE2 increases the fermentation rate of some wine-producing strains of S. cerevisiae. In this work, we investigated the effect of URE2 deletion (ΔURE2) on the metabolism of S. cerevisiae. During growth on glucose, the ΔURE2 mutant grew less well than the wild type; however, it produced ethanol at higher rates. To better under the behavior of this mutant, we performed transcriptomics and metabolomics. Analysis of the RNA sequencing results and metabolite levels indicate that the mutant strain exhibited characteristics of both nitrogen starvation and autophagy. In addition, many pyruvate decarboxylase and alcohol dehydrogenase isoforms were expressed at higher rates than the wild type. The mutant also accumulated less trehalose and glycogen, and produced more lipids. These results suggest that URE2 may be a promising target for metabolic engineering in S. cerevisiae and potentially other strains of yeast as well for the production of lipid-based fuels and chemicals.

59 BASIC BIOLOGICAL SCIENCES↗

Systems analysis of Lipomyces starkeyi during growth on various plant-based sugars

Oleaginous yeasts have received significant attention due to their substantial lipid storage capability. The accumulated lipids can be utilized directly or processed into various bioproducts and biofuels. Lipomyces starkeyi is an oleaginous yeast capable of using multiple plant-based sugars, such as glucose, xylose, and cellobiose. It is, however, a relatively unexplored yeast due to limited knowledge about its physiology. In this study, we have evaluated the growth of L. starkeyi on different sugars and performed transcriptomic and metabolomic analyses to understand the underlying mechanisms of sugar metabolism. Principal component analysis showed clear differences resulting from growth on different sugars. We have further reported various metabolic pathways activated during growth on these sugars. We also observed non-specific regulation in L. starkeyi and have updated the gene annotations for the NRRL Y-11557 strain. Furthermore, this analysis provides a foundation for understanding the metabolism of these plant-based sugars and potentially valuable information to guide the metabolic engineering of L. starkeyi to produce bioproducts and biofuels.

59 BASIC BIOLOGICAL SCIENCES↗

Differential DNA methylation and metabolite profiling of Atlantic killifish (Fundulus heteroclitus) from the New Bedford Harbor Superfund site

Atlantic killifish (Fundulus heteroclitus) is a valuable model in evolutionary toxicology to study how the interactions between genetic and environmental factors serve the adaptive ability of organisms to resist chemical pollution. Killifish populations inhabiting environmental toxicant-contaminated New Bedford Harbor (NBH) show phenotypes tolerant to polychlorinated biphenyls (PCBs) and differences at the transcriptional and genomic levels. However, limited research has explored epigenetic alterations and metabolic effects in NBH killifish. To identify the involvement of epigenetic and metabolic regulation in the adaptive response of killifish, we investigated tissue- and sex-specific differences in global DNA methylation and metabolomic profiles of NBH killifish populations, compared to sensitive populations from a non-polluted site, Scorton Creek (SC). The results revealed that liver-specific global DNA hypomethylation and differential metabolites were evident in fish from NBH compared with those from SC. The sex-specific differences were not greater than the tissue-specific differences. We demonstrated liver-specific enriched metabolic pathways (e.g., amino acid metabolic pathways converged into the urea cycle and glutathione metabolism), suggesting possible crosstalk between differential metabolites and DNA hypomethylation in the livers of NBH killifish. Additional investigation of methylated gene regions is necessary to understand the functional role of DNA hypomethylation in the regulation of enzyme-encoding genes associated with metabolic processes and physiological changes in NBH populations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Isolation and characterization of microalgae strains able to grow on complex biomass hydrolysate for industrial application

Producing algae biomass economically remains one of the chief bottlenecks for commercializing algae products. The aim of this work is to identify new strains of algae that can grow on cost effective media derived from cellulosic waste streams, characterize the potential of these strains to produce compounds of high industrial value, and identify those strains capable of facile genetic transformation. Here we report, out of 45 strains initially isolated, three were selected based on their ability to efficiently grow on organic waste material (corn stover hydrolysate) as a carbon source; Chlorococcum sp., Desmodesmus sp., and Chlamydomonas debaryana. Untargeted metabolomics was performed on each strain, identifying several metabolites of high relative abundances that are of commercial interest, such as lactic acid, butane-2,3-diol, amino acids, tartaric acid, triacylglycerols, and lipid species containing different, mono- and polyunsaturated fatty acids, depending on the strain and growth condition. The strains also produced carbohydrates of industrial relevance. Chlorococcum sp. was found to be genetically transformable using standard simple transformation protocols. These results suggest that with further development, these strains could open the door to economic production of high value commercial compounds utilizing waste streams from cellulosic biomass.

09 BIOMASS FUELS↗

Histopathologic and proteogenomic heterogeneity reveals features of clear cell renal cell carcinoma aggressiveness

Clear cell renal cell carcinomas (ccRCCs) represent ∼75% of RCC cases and account for most RCC-associated deaths. Inter- and intratumoral heterogeneity (ITH) results in varying prognosis and treatment outcomes. To obtain the most comprehensive profile of ccRCC, we perform integrative histopathologic, proteogenomic, and metabolomic analyses on 305 ccRCC tumor segments and 166 paired adjacent normal tissues from 213 cases. Combining histologic and molecular profiles reveals ITH in 90% of ccRCCs, with 50% demonstrating immune signature heterogeneity. High tumor grade, along with BAP1 mutation, genome instability, increased hypermethylation, and a specific protein glycosylation signature define a high-risk disease subset, where UCHL1 expression displays prognostic value. Single-nuclei RNA sequencing of the adverse sarcomatoid and rhabdoid phenotypes uncover gene signatures and potential insights into tumor evolution. In vitro cell line studies confirm the potential of inhibiting identified phosphoproteome targets. This study molecularly stratifies aggressive histopathologic subtypes that may inform more effective treatment strategies.

CPTAC↗

Leveraging hyperspectral phenotyping for accurate, non-destructive prediction of metabolite profiles in poplar under drought stress

Accurately predicting drought tolerance in woody perennial bioenergy crops is critical for sustainable biomass production under fluctuating precipitation. Hyperspectral imaging (HSI) in the visible-near-infrared (VNIR) and shortwave-infrared (SWIR) ranges offers a promising approach for predicting plant biochemical traits, yet its application in metabolite profiling remains underexplored. We integrated VNIR+SWIR HSI with untargeted metabolomics to investigate drought-induced metabolic shifts in Populus leaves from eight Populus genotypes. Metabolite profiling identified 127 compounds, with 73 showing significant drought responses spanning amino acids (AA), carbohydrates (CHO), phenolic glycosides (PG), organic acids (OA), fatty acids and alcohols (FA), terpenes (T), phenolic metabolites (P), and unclassified metabolites. Spectral analysis revealed consistently higher reflectance across VNIR and SWIR wavelengths in drought-stressed plants, corresponding with increased accumulation of AA and reduced CHO and PG levels. Least absolute shrinkage and selection operator (LASSO) regression modeling identified robust spectral predictors of metabolite concentrations, associating VNIR wavelengths (500–700 nm) predominantly with AA and P, whereas SWIR wavelengths (1680–1700 nm) reliably predicted CHO, OA, and T. Several stable spectral-metabolite associations persisted across the two watering regimes (drought vs. well-watered), highlighting their potential as spectral biomarkers for non-destructive stress monitoring. Minimal genotype-specific variation suggests that observed spectral and metabolic responses were driven primarily by environmental factors, likely reflecting limited genetic diversity among the commercial Populus genotypes examined. This work establishes VNIR+SWIR hyperspectral imaging as a powerful, non-destructive phenotyping tool for precision monitoring and targeted improvement of drought resilience in bioenergy crops.

Biochemical trait prediction↗

Spatial evidence of cryptic methane cycling and methylotrophic metabolisms along a land–ocean transect in salt marsh sediment

Methylotrophic methanogenesis in the sulfate-rich zone of coastal and marine sediments couples with anaerobic oxidation of methane (AOM), forming the cryptic methane cycle. This study provides evidence of cryptic methane cycling in the sulfate-rich zone across a land–ocean transect of four stations–two brackish, one marine, and one hypersaline–within the Carpinteria Salt Marsh Reserve (CSMR), southern California, USA. Samples from the top 20 cm of sediment from the transect were analyzed through geochemical and molecular (16S rRNA) techniques, in-vitro methanogenesis incubations, and radiotracer incubations utilizing 35 S-SO 4 , 14 C-mono-methylamine, and 14 C-CH 4 . Sediment methane concentrations were consistently low (3 to 28 µM) at all stations, except for the marine station, where methane increased with depth reaching 665 µM. Methanogenesis from mono-methylamine was detected throughout the sediment at all stations with estimated CH 4 production rates in the sub-nanomolar to nanomolar range per cm 3 sediment and day. 16S rRNA analysis identified methanogenic archaea (Methanosarcinaceae, Methanomassiliicoccales, and Methanonatronarchaeacea) capable of producing methane from methylamines in sediment where methylotrophic methanogenesis was found to be active. Metabolomic analysis of porewater showed mono-methylamine was mostly undetectable (<3 µM) or present in trace amounts (<10 µM) suggesting rapid metabolic turnover. In-vitro methanogenesis incubations of natural sediment showed no linear methane buildup, suggesting a process limiting methane emissions. AOM activity, measured with 14 C-CH 4 , overlapped with methanogenesis from mono-methylamine activity at all stations, with rates ranging from 0.03 to 19.4 nmol cm −3 d −1 . Geochemical porewater analysis showed the CSMR sediments are rich in sulfate and iron. Porewater sulfate concentrations (9–91 mM) were non-limiting across the transect, supporting sulfate reduction activity (1.5–2,506 nmol cm −3 d −1 ). Porewater sulfide and iron (II) profiles indicated that the sediment transitioned from a predominantly iron-reducing environment at the two brackish stations to a predominantly sulfate-reducing environment at the marine and hypersaline stations, which coincided with the presence of phyla (Desulfobacterota) involved in these processes. AOM activity overlapped with sulfate reduction and porewater iron (II) concentrations suggesting that AOM is likely coupled to sulfate and possibly iron reduction at all stations. However, 16S rRNA analysis identified anaerobic methanotrophs (ANME-2) only at the marine and hypersaline stations while putative methanogens were found in sediment across all stations. In one sediment horizon at the marine station, methanogen families (Methanosarcinaceae, Methanosaetaceae, Methanomassiliicoccales, and Methanoregulaceae) and ANME 2a,2b, and 2c groups were found together. Collectively, our data suggest that at the brackish stations methanogens alone may be involved in cryptic methane cycling, while at the marine and hypersaline stations both groups may be involved in the process. Differences in rate constants from incubations with 14 C-labeled methane and mono-methylamine suggest a non-methanogenic process oxidizing mono-methylamine to inorganic carbon, likely mediated by sulfate-reducing bacteria. Understanding the potential competition of sulfate reducers with methanogens for mono-methylamine needs further investigation as it might be another important process responsible for low methane emissions in salt marshes.

Anaerobic oxidation of methane↗

Characterization of the Entry Steps in Diterpenoid Alkaloid Biosynthesis

The diterpenoid alkaloids are a group of specialized metabolites where the terpenoid and alkaloid classes intersect, and which are found primarily within the Aconitum (Wolf’s-Bane) and Delphinium (Larkspur) genera. While there is considerable interest in these compounds for their wide range of bioactivities, their structural complexity poses a significant challenge for chemical synthesis. Biosynthesis offers an appealing alternative for production, however, little progress has been made towards elucidation of their biosynthetic pathways. Here, we employ a comparative transcriptomics approach to identify six enzymatic steps in the biosynthesis of atisinium, conserved across both Delphinium grandiflorum and Aconitum plicatum . Key to this pathway is a reductase which selectively incorporates ethanolamine over ethylamine into the diterpenoid scaffold. While the majority of diterpenoid alkaloids contain an ethylamine moiety, we demonstrate through isotope labeling in Aconitum callus cultures and a computational metabolomics approach that ethanolamine is, unintuitively, the preferred source of nitrogen for these metabolites. Identification of these enzymes and production of a key intermediate in a heterologous host paves the way for biosynthetic production of this group of metabolites with promise for medicinal applications.

biosynthesis↗

Insight into industrial hemp ( Cannabis sativa L.) root exudation composition in a simulated soil environment: a rhizosphere-on-a-chip study

Microfluidic technologies provide a reduced complexity and soil-free environment to study plant-soil interactions at the microscale. Traditionally used for model plants such as Arabidopsis thaliana, this study represents the first application of a rhizosphere-on-a-chip (RhizoChip) to investigate root exudation in industrial hemp (Cannabis sativa L.), an agronomic crop with growing economic importance. By incorporating soil-like minerals (kaolinite, potassium feldspar, and biotite), the RhizoChip addresses limitations of previous research. Hemp seedlings grown in mineral-containing chips exhibited significant root growth, emphasizing the critical role of minerals in root development. Using untargeted metabolomics, 170 compounds were identified, including organic acids, amino acids, and secondary metabolites, with distinct profiles across conditions. Metabolic pathway analysis revealed activity in amino acid metabolism, the citric acid cycle, and secondary metabolite biosynthesis. In conclusion, this study highlights the RhizoChip's potential for long-term studies of root exudates in non-model crops and offers insights into rhizosphere processes with implications for sustainable agriculture.

59 BASIC BIOLOGICAL SCIENCES↗