Exserolide J ameliorates lipid accumulation in vitro by regulating liver X receptor alpha and peroxisome proliferator-activated receptor alpha proteins.

Exserolides are isocoumarin derivatives containing lactone moiety. Recently, some isocoumarins have been demonstrated to ameliorate hyperlipidemia, a major factor for inducing cardiovascular diseases. However, the effects and mechanisms of action of exserolides on hyperlipidemia are not known. The aim of this study is to investigate whether the marine fungus Setosphaeria sp.-derived exserolides (compounds I, J, E, and F) exert lipid-lowering effects via improving reverse cholesterol transport (RCT) in vitro. RAW264.7 macrophages and HepG2 cells were used to establish lipid-laden models, and the levels of intracellular lipids and RCT-related proteins were determined by assay kits and Western blotting, respectively. We observed that exserolides (at a 5 µM concentration) significantly decreased intracellular cholesterol and triglyceride levels in oxidized low-density lipoprotein-laden RAW264.7 cells and markedly improved [3H]-cholesterol efflux. Among the four tested compounds, exserolide J increased the protein levels of ATP-binding cassette transporter A1, peroxisome proliferator-activated receptor α (PPARα), and liver X receptor α (LXRα). Furthermore, treatment with exserolides significantly decreased oleic acid-laden lipid accumulation in HepG2 hepatocytes. Mechanistically, exserolides enhance PPARα protein levels; furthermore, compound J increases cholesterol 7 alpha-hydroxylase A1 and LXRα protein levels. Molecular docking revealed that exserolides, particularly compound J, can interact with PPARα and LXRα proteins. These data suggest that the terminal carboxyl group of compound J plays a key role in lowering lipid levels by stimulating LXRα and PPARα proteins. In conclusion, compound J exhibits powerful lipid-lowering effects in vitro. However, its hypolipidemic effects in vivo should be investigated in the future.

Identification of biological signatures of cruciferous vegetable consumption utilizing machine learning-based global untargeted stable isotope traced metabolomics.

In recent years there has been increased interest in identifying biological signatures of food consumption for use as biomarkers. Traditional metabolomics-based biomarker discovery approaches rely on multivariate statistics which cannot differentiate between host- and food-derived compounds, thus novel approaches to biomarker discovery are required to advance the field. To this aim, we have developed a new method that combines global untargeted stable isotope traced metabolomics and a machine learning approach to identify biological signatures of cruciferous vegetable consumption. Participants consumed a single serving of broccoli (n = 16), alfalfa sprouts (n = 16) or collard greens (n = 26) which contained either control unlabeled metabolites, or that were grown in the presence of deuterium-labeled water to intrinsically label metabolites. Mass spectrometry analysis indicated 133 metabolites in broccoli sprouts and 139 metabolites in the alfalfa sprouts were labeled with deuterium isotopes. Urine and plasma were collected and analyzed using untargeted metabolomics on an AB SCIEX TripleTOF 5,600 mass spectrometer. Global untargeted stable isotope tracing was completed using openly available software and a novel random forest machine learning based classifier. Among participants who consumed labeled broccoli sprouts or collard greens, 13 deuterium-incorporated metabolomic features were detected in urine representing 8 urine metabolites. Plasma was analyzed among collard green consumers and 11 labeled features were detected representing 5 plasma metabolites. These deuterium-labeled metabolites represent potential biological signatures of cruciferous vegetables consumption. Isoleucine, indole-3-acetic acid-N-O-glucuronide, dihydrosinapic acid were annotated as labeled compounds but other labeled metabolites could not be annotated. This work presents a novel framework for identifying biological signatures of food consumption for biomarker discovery. Additionally, this work presents novel applications of metabolomics and machine learning in the life sciences.

De novo and salvage purine synthesis pathways across tissues and tumors.

Purine nucleotides are vital for RNA and DNA synthesis, signaling, metabolism, and energy homeostasis. To synthesize purines, cells use two principal routes: the de novo and salvage pathways. Traditionally, it is believed that proliferating cells predominantly rely on de novo synthesis, whereas differentiated tissues favor the salvage pathway. Unexpectedly, we find that adenine and inosine are the most effective circulating precursors for supplying purine nucleotides to tissues and tumors, while hypoxanthine is rapidly catabolized and poorly salvaged in vivo. Quantitative metabolic analysis demonstrates comparative contribution from de novo synthesis and salvage pathways in maintaining purine nucleotide pools in tumors. Notably, feeding mice nucleotides accelerates tumor growth, while inhibiting purine salvage slows down tumor progression, revealing a crucial role of the salvage pathway in tumor metabolism. These findings provide fundamental insights into how normal tissues and tumors maintain purine nucleotides and highlight the significance of purine salvage in cancer.

Stable Isotope Tracing Analysis in Cancer Research: Advancements and Challenges in Identifying Dysregulated Cancer Metabolism and Treatment Strategies.

Metabolic reprogramming is a hallmark of cancer, driving the development of therapies targeting cancer metabolism. Stable isotope tracing has emerged as a widely adopted tool for monitoring cancer metabolism both in vitro and in vivo. Advances in instrumentation and the development of new tracers, metabolite databases, and data analysis tools have expanded the scope of cancer metabolism studies across these scales. In this review, we explore the latest advancements in metabolic analysis, spanning from experimental design in stable isotope-labeling metabolomics to sophisticated data analysis techniques. We highlight successful applications in cancer research, particularly focusing on ongoing clinical trials utilizing stable isotope tracing to characterize disease progression, treatment responses, and potential mechanisms of resistance to anticancer therapies. Furthermore, we outline key challenges and discuss potential strategies to address them, aiming to enhance our understanding of the biochemical basis of cancer metabolism.

The differential assimilation of nitrogen fertilizer compounds by soil microorganisms.

The differential soil microbial assimilation of common nitrogen (N) fertilizer compounds into the soil organic N pool is revealed using novel compound-specific amino acid (AA) 15N-stable isotope probing. The incorporation of fertilizer 15N into individual AAs reflected the known biochemistry of N assimilation-e.g. 15N-labelled ammonium (15NH4+) was assimilated most quickly and to the greatest extent into glutamate. A maximum of 12.9% of applied 15NH4+, or 11.7% of 'retained' 15NH4+ (remaining in the soil) was assimilated into the total hydrolysable AA pool in the Rowden Moor soil. Incorporation was lowest in the Rowden Moor 15N-labelled nitrate (15NO3-) treatment, at 1.7% of applied 15N or 1.6% of retained 15N. Incorporation in the 15NH4+ and 15NO3- treatments in the Winterbourne Abbas soil, and the 15N-urea treatment in both soils was between 4.4% and 6.5% of applied 15N or 5.2% and 6.4% of retained 15N. This represents a key step in greater comprehension of the microbially mediated transformations of fertilizer N to organic N and contributes to a more complete picture of soil N-cycling. The approach also mechanistically links theoretical/pure culture derived biochemical expectations and bulk level fertilizer immobilization studies, bridging these different scales of understanding.

Quantifying acyl-chain diversity in isobaric compound lipids containing monomethyl branched-chain fatty acids.

Compound lipids comprise a diverse group of metabolites present in living systems, and metabolic- and environmentally-driven structural distinctions across this family is increasingly linked to biological function. However, methods for deconvoluting these often isobaric lipid species are lacking or require specialized instrumentation. Notably, acyl-chain diversity within cells may be influenced by nutritional states, metabolic dysregulation, or genetic alterations. Therefore, a reliable, validated method of quantifying structurally similar even-, odd-, and branched-chain acyl groups within intact compound lipids will be invaluable for gaining molecular insights into their biological functions. Here we demonstrate the chromatographic resolution of isobaric lipids containing distinct combinations of straight-chain and branched-chain acyl groups via ultra-high-pressure liquid chromatography (UHPLC)-mass spectrometry (MS) using a C30 liquid chromatography column. Using metabolically-engineered adipocytes lacking branched-keto acid dehydrogenase A (Bckdha), we validate this approach through a combination of fatty acid supplementation and metabolic tracing using monomethyl branched-chain fatty acids and valine. We observe resolution of numerous isobaric triacylglycerols and other compound lipids, demonstrating the resolving utility of this method. This approach strengthens our ability to quantify and characterize the inherent diversity of acyl chains across the lipidome.

Variation in Nitrogen Utilization and Nutrient Composition across Various Organs under Different Strip Logging Management Models in Moso Bamboo (Phyllostachys edulis) Forest.

The rapid restoration and renewal of the moso bamboo logging zone after strip logging has emerged as a key research area, particularly regarding whether nutrient accumulation and utilization in reserve zones can aid in the restoration and regeneration of the logging zone. In this study, a dynamic 15N isotope tracking experiment was conducted by injecting labeled urea fertilizer into bamboo culms. Logging zones and reserve zones of 6 m, 8 m, and 10 m widths were established. The conventional selective logging treatment served as a control (Con). Measurements were taken in May and October to assess the differences in nitrogen accumulation ability, utilization rates, and nutrient content across different organs in bamboo forests at different growth stages and under different treatments. Principal component analysis was conducted to evaluate and determine the importance of each indicator and strip logging treatment comprehensively. The results showed that various bamboo organs exhibited higher nitrogen accumulation and utilization rates during the peak growth period compared to the late growth period. Leaves had the highest nitrogen accumulation and utilization rates than the other organs. The average C content in various bamboo organs under different logging treatments exhibited subtle differences, irrespective of variation in logging width treatments. Bamboo culm exhibited the highest carbon accumulation. The C content in various bamboo organs was higher during the peak growth period than in the late growth period. The nitrogen content peaked in the leaves during the two growth stages and was significantly higher compared to the other organs. Most bamboo organs in the logging zones exhibited relatively higher nitrogen content than in the reserve zone and Con group. The P content was highest in bamboo leaves compared with other organs across the different strip logging treatments. Principal component analysis revealed relatively high absolute values of the coefficients for the C content, bamboo stump C content, and culm Ndff%. Log8 and Res10 zones had the highest comprehensive evaluation scores, indicating that Log8 and Res10 had the best effect on the promotion of nitrogen utilization and nutrient accumulation in various organs of moso bamboo.

Ex-Vivo 13C NMR Spectroscopy of Rodent Brain: TNF Restricts Neuronal Utilization of Astrocyte-Derived Metabolites.

Tumor necrosis factor (TNF) has well-established roles in neuroinflammatory disorders, but the effect of TNF on the biochemistry of brain cells remains poorly understood. Here, we microinjected TNF into the brain to study its impact on glial and neuronal metabolism (glycolysis, pentose phosphate pathway, citric acid cycle, pyruvate dehydrogenase, and pyruvate carboxylase pathways) using 13C NMR spectroscopy on brain extracts following intravenous [1,2-13C]-glucose (to probe glia and neuron metabolism), [2-13C]-acetate (probing astrocyte-specific metabolites), or [3-13C]-lactate. An increase in [4,5-13C]-glutamine and [2,3-13C]-lactate coupled with a decrease in [4,5-13C]-glutamate was observed in the [1,2-13C]-glucose-infused animals treated with TNF. As glutamine is produced from glutamate by astrocyte-specific glutamine synthetase the increase in [4,5-13C]-glutamine reflects increased production of glutamine by astrocytes. This was confirmed by infusion with astrocyte substrate [2-13C]-acetate. As lactate is metabolized in the brain to produce glutamate, the simultaneous increase in [2,3-13C]-lactate and decrease in [4,5-13C]-glutamate suggests decreased lactate utilization, which was confirmed using [3-13C]-lactate as a metabolic precursor. These results suggest that TNF rearranges the metabolic network, disrupting the energy supply chain perturbing the glutamine-glutamate shuttle between astrocytes and the neurons. These insights pave the way for developing astrocyte-targeted therapeutic strategies aimed at modulating effects of TNF to restore metabolic homeostasis in neuroinflammatory disorders.

Phospholipid isotope tracing suggests ß-catenin-driven suppression of phosphatidylcholine metabolism in hepatocellular carcinoma.

Activating mutations in the CTNNB1 gene encoding ß-catenin are among the most frequently observed oncogenic alterations in hepatocellular carcinoma (HCC). Profound alterations in lipid metabolism, including increases in fatty acid oxidation and transformation of the phospholipidome, occur in HCC with CTNNB1 mutations, but it is unclear what mechanisms give rise to these changes. We employed untargeted lipidomics and targeted isotope tracing to measure phospholipid synthesis activity in an inducible human liver cell line expressing mutant ß-catenin, as well as in transgenic zebrafish with activated ß-catenin-driven HCC. In both models, activated ß-catenin expression was associated with large changes in the lipidome including conserved increases in acylcarnitines and ceramides and decreases in triglycerides. Lipid isotope tracing analysis in human cells revealed a reduction in phosphatidylcholine (PC) production rates as assayed by choline incorporation. We developed lipid isotope tracing analysis for zebrafish tumors and observed reductions in phosphatidylcholine synthesis by both the CDP-choline and PEMT pathways. The observed changes in the ß-catenin-driven HCC phospholipidome suggest that zebrafish can recapitulate conserved features of HCC lipid metabolism and may serve as a model for identifying future HCC-specific lipid metabolic targets.

Identification of high sugar diet-induced dysregulated metabolic pathways in muscle using tissue-specific metabolic models in Drosophila.

Individual tissues perform highly specialized metabolic functions to maintain whole-body homeostasis. Although Drosophila serves as a powerful model for studying human metabolic diseases, a lack of tissue-specific metabolic models makes it challenging to quantitatively assess the metabolic processes of individual tissues and disease models in this organism. To address this issue, we reconstructed 32 tissue-specific genome-scale metabolic models (GEMs) using pseudo-bulk single cell transcriptomics data, revealing distinct metabolic network structures across tissues. Leveraging enzyme kinetics and flux analyses, we predicted tissue-dependent metabolic pathway activities, recapitulating known tissue functions and identifying tissue-specific metabolic signatures, as supported by metabolite profiling. Moreover, to demonstrate the utility of tissue-specific GEMs in a disease context, we examined the effect of a high sugar diet (HSD) on muscle metabolism. Together with 13C-glucose isotopic tracer studies, we identified glyceraldehyde 3-phosphate dehydrogenase (GAPDH) as a rate-limiting enzyme in response to HSD. Mechanistically, the decreased GAPDH activity was linked to elevated NADH/NAD+ ratio, caused by disturbed NAD+ regeneration rates, and oxidation of GAPDH. Furthermore, we introduced a pathway flux index to predict and validate additionally perturbed pathways, including fructose and butanoate metabolism. Altogether, our results represent a significant advance in generating quantitative tissue-specific GEMs and flux analyses in Drosophila, highlighting their use for identifying dysregulated metabolic pathways and their regulation in a human disease model.

Direct Infusion Mass Spectrometry to Rapidly Map Metabolic Flux of Substrates Labeled with Stable Isotopes.

Direct infusion-high-resolution mass spectrometry (DI-HRMS) allows for rapid profiling of complex mixtures of metabolites in blood, cerebrospinal fluid, tissue samples and cultured cells. Here, we present a DI-HRMS method suitable for the rapid determination of metabolic fluxes of isotopically labeled substrates in cultured cells and organoids. We adapted an automated annotation pipeline by selecting labeled adducts that best represent the majority of 13C and/or 15N-labeled glycolytic and tricarboxylic acid cycle intermediates as well as a number of their derivatives. Furthermore, valine, leucine and several of their degradation products were included. We show that DI-HRMS can determine anticipated and unanticipated alterations in metabolic fluxes along these pathways that result from the genetic alteration of single metabolic enzymes, including pyruvate dehydrogenase (PDHA1) and glutaminase (GLS). In addition, it can precisely pinpoint metabolic adaptations to the loss of methylmalonyl-CoA mutase in patient-derived liver organoids. Our results highlight the power of DI-HRMS in combination with stable isotopically labeled compounds as an efficient screening method for fluxomics.

Epstein-Barr-Virus-Driven Cardiolipin Synthesis Sustains Metabolic Remodeling During B-cell Lymphomagenesis.

Epstein-Barr Virus (EBV) is associated with a range of B-cell malignancies, including Burkitt, Hodgkin, post-transplant, and AIDS-related lymphomas. Studies highlight EBV's transformative capability to induce oncometabolism in B-cells to support energy, biosynthetic precursors, and redox equivalents necessary for transition from quiescent to proliferation. Mitochondrial dysfunction presents an intrinsic barrier to EBV B-cell immortalization. Yet, how EBV maintains B-cell mitochondrial function and metabolic fluxes remains unclear. Here we show that EBV boosts cardiolipin(CL) biosynthesis, essential for mitochondrial cristae biogenesis, via EBNA2-induced CL enzyme transactivation. Pharmaceutical and CRISPR genetic analyses underscore the essentiality of CL biosynthesis in EBV-transformed B-cells. Metabolomic and isotopic tracing highlight CL's role in sustaining respiration, one-carbon metabolism, and aspartate synthesis, all vital for EBV-transformed B-cells. Targeting CL biosynthesis destabilizes mitochondrial one-carbon enzymes, causing synthetic lethality when coupled with a SHMT1/2 inhibitor. We demonstrate EBV-induced CL metabolism as a therapeutic target, offering new strategies against EBV-associated B-cell malignancies.

Elevated nutrient availability enhances chondrocyte metabolism and biosynthesis in tissue-engineered cartilage.

OBJECTIVE: Chondrocytes, which typically rely on anaerobic metabolism, exhibit upregulated biosynthetic activity when subjected to conditions that elicit mixed aerobic-anaerobic metabolism. Previously, we observed that increasing media volume resulted in the transition from anaerobic to mixed aerobic-anaerobic metabolism. Maximal extracellular matrix (ECM) accumulation occurred at this transition as a result of changes in hypoxia-inducible factor 1α signaling and associated hypoxic gene expression. This study aimed to explore the effect of further increases in media availability on ECM synthesis and chondrocyte metabolism. METHODS: Primary bovine chondrocytes were grown in 3D high-density tissue culture under varying levels of media availability (4-16 mL/106 cells). Changes in ECM accumulation and metabolism were determined through biochemical assays and 13C-metabolic flux analysis (13C-MFA). RESULTS: Increasing media volumes resulted in higher accumulation of cartilaginous ECM (collagen and proteoglycans) and cellularity. Extracellular metabolite measurements revealed that elevated media availability led to increased glucose and glutamine metabolism, along with increased anaerobic activity. 13C-MFA utilizing [U-13C] glucose demonstrated that increased media availability significantly impacted central carbon metabolism, upregulating all glucose-related metabolic pathways (glycolysis, lactate fermentation, the tricarboxylic acid (TCA) cycle, hexosamine biosynthetic pathway, and the malate-aspartate shuttle). Furthermore, 13C-MFA indicated that glutamine was donating carbons to the TCA cycle, and additional studies involving [U-13C] glutamine tracing supported this notion. CONCLUSIONS: Elevated media availability upregulates ECM synthesis and leads to significant changes in metabolic phenotype. Glutamine plays an important role in chondrocyte metabolism and increases in glutamine metabolism correlate with increases in ECM accumulation.

Bioconcentration of Inorganic and Methyl Mercury by Algae Revealed Using Dual-Mass Single-Cell ICP-MS with Double Isotope Tracers.

Algae are an entry point for mercury (Hg) into the food web. Bioconcentration of Hg by algae is crucial for its biogeochemical cycling and environmental risk. Herein, considering the cell heterogeneity, we investigated the bioconcentration of coexisting isotope-labeled inorganic (199IHg) and methyl Hg (201MeHg) by six typical freshwater and marine algae using dual-mass single-cell inductively coupled plasma mass spectrometry (scICP-MS). First, a universal pretreatment procedure for the scICP-MS analysis of algae was developed. Using the proposed method, the intra- and interspecies heterogeneities and the kinetics of Hg bioconcentration by algae were revealed at the single-cell level. The heterogeneity in the cellular Hg contents is largely related to cell size. The bioconcentration process reached a dynamic equilibrium involving influx/adsorption and efflux/desorption within hours. Algal density is a key factor affecting the distribution of Hg between algae and ambient water. Cellular Hg contents were negatively correlated with algal density, whereas the volume concentration factors almost remained constant. Accordingly, we developed a model based on single-cell analysis that well describes the density-driven effects of Hg bioconcentration by algae. From a novel single-cell perspective, the findings improve our understanding of algal bioconcentration governed by various biological and environmental factors.

Selected Ion Monitoring for Orbitrap-Based Metabolomics.

Orbitrap mass spectrometry in full scan mode enables the simultaneous detection of hundreds of metabolites and their isotope-labeled forms. Yet, sensitivity remains limiting for many metabolites, including low-concentration species, poor ionizers, and low-fractional-abundance isotope-labeled forms in isotope-tracing studies. Here, we explore selected ion monitoring (SIM) as a means of sensitivity enhancement. The analytes of interest are enriched in the orbitrap analyzer by using the quadrupole as a mass filter to select particular ions. In tissue extracts, SIM significantly enhances the detection of ions of low intensity, as indicated by improved signal-to-noise (S/N) ratios and measurement precision. In addition, SIM improves the accuracy of isotope-ratio measurements. SIM, however, must be deployed with care, as excessive accumulation in the orbitrap of similar m/z ions can lead, via space-charge effects, to decreased performance (signal loss, mass shift, and ion coalescence). Ion accumulation can be controlled by adjusting settings including injection time and target ion quantity. Overall, we suggest using a full scan to ensure broad metabolic coverage, in tandem with SIM, for the accurate quantitation of targeted low-intensity ions, and provide methods deploying this approach to enhance metabolome coverage.

Methylotrophic methanogenesis in the Archaeoglobi revealed by cultivation of Ca. Methanoglobus hypatiae from a Yellowstone hot spring.

Over the past decade, environmental metagenomics and polymerase chain reaction-based marker gene surveys have revealed that several lineages beyond just a few well-established groups within the Euryarchaeota superphylum harbor the genetic potential for methanogenesis. One of these groups are the Archaeoglobi, a class of thermophilic Euryarchaeota that have long been considered to live non-methanogenic lifestyles. Here, we enriched Candidatus Methanoglobus hypatiae, a methanogen affiliated with the family Archaeoglobaceae, from a hot spring in Yellowstone National Park. The enrichment is sediment-free, grows at 64-70°C and a pH of 7.8, and produces methane from mono-, di-, and tri-methylamine. Ca. M. hypatiae is represented by a 1.62 Mb metagenome-assembled genome with an estimated completeness of 100% and accounts for up to 67% of cells in the culture according to fluorescence in situ hybridization. Via genome-resolved metatranscriptomics and stable isotope tracing, we demonstrate that Ca. M. hypatiae expresses methylotrophic methanogenesis and energy-conserving pathways for reducing monomethylamine to methane. The detection of Archaeoglobi populations related to Ca. M. hypatiae in 36 geochemically diverse geothermal sites within Yellowstone National Park, as revealed through the examination of previously published gene amplicon datasets, implies a previously underestimated contribution to anaerobic carbon cycling in extreme ecosystems.

Sources apportionments of heavy metal(loid)s in the farmland soils close to industrial parks: Integrated application of positive matrix factorization (PMF) and cadmium isotopic fractionation.

Understanding the source identification and distribution of heavy metal(loid)s in soil is essential for risk management. The sources of heavy metal(loid)s in farmland soil, especially in areas with rapid economic development, were complicated and need to be explored urgently. This study combined geographic information system (GIS) mapping, positive matrix factorization (PMF) model and cadmium (Cd) isotope fingerprinting methods to identify heavy metal(loid) sources in a typical town in the economically developed Yangtze River Delta region of China. Cd, As, Cu, Zn, Pb, Ni and Co in different samples were detected. The results showed that Cd was the most severely contaminated element, with an exceedance rate of 78.0 %. GIS mapping results indicated that the hotspot area was located in the northeastern area with prolonged operational histories of electroplating and non-ferrous metal smelting industries. The PMF model analysis also identified emissions from smelting and electroplating enterprises as the main sources of Cd in the soil, counted for 49.28 %, followed by traffic (25.66 %) and agricultural (25.06 %) sources. Through further isotopic analysis, it was found that in soil samples near the industrial park, the contribution of electroplating and non-ferrous metal smelting enterprises to cadmium pollution was significantly higher than other regions. The integrated use of various methodologies allows for precise analysis of sources and input pathways, offering valuable insights for future pollution control and soil remediation endeavors.

Cadmium, zinc, and copper leaching rates determined in large monolith lysimeters.

Soil mass balances are used to assess the risk of trace metals that are inadvertently applied with fertilizers into agroecosystems. The accuracy of such balances is limited by leaching rates, as they are difficult to measure. Here, we used monolith lysimeters to precisely determine Cd, Cu, and Zn leaching rates in 2021 and 2022. The large lysimeters (n = 12, 1 m diameter, 1.35 m depth) included one soil type (cambisol, weakly acidic) and distinct cropping systems with three experimental replicates. Stable isotope tracers were applied to determine the direct transfer of these trace metals from the soil surface into the seepage water. The annual leaching rates ranged from 0.04 to 0.30 for Cd, 2.65 to 11.7 for Cu, and 7.27 to 39.0 g (ha a)-1 for Zn. These leaching rates were up to four times higher in the year with several heavy rain periods compared to the dry year. Monthly resolved data revealed that distinct climatic conditions in combination with crop development have a strong impact on trace metal leaching rates. In contrast, fertilization strategy (e.g., conventional vs. organic) had a minor effect on leaching rates. Trace metal leaching rates were up to 10 times smaller than fertilizer inputs and had therefore a minor impact on soil mass balances. This was further confirmed with isotope source tracing that showed that only small fractions of Cd, Cu, and Zn were directly transferred from the soil surface to the leached seepage water within two years (< 0.07 %). A comparison with models that predict Cd leaching rates in the EU suggests that the models overestimate the Cd soil output with seepage water. Hence, monolith lysimeters can help to refine leaching models and thereby also soil mass balances that are used to assess the risk of trace metals inputs with fertilizers.

13C-SpaceM: Spatial single-cell isotope tracing reveals heterogeneity of de novo fatty acid synthesis in cancer.

Metabolism has emerged as a key factor in homeostasis and disease including cancer. Yet, little is known about the heterogeneity of metabolic activity of cancer cells due to the lack of tools to directly probe it. Here, we present a novel method, 13C-SpaceM for spatial single-cell isotope tracing of glucose-dependent de novo lipogenesis. The method combines imaging mass spectrometry for spatially-resolved detection of 13C6-glucose-derived 13C label incorporated into esterified fatty acids with microscopy and computational methods for data integration and analysis. We validated 13C-SpaceM on a spatially-heterogeneous normoxia-hypoxia model of liver cancer cells. Investigating cultured cells, we revealed single-cell heterogeneity of lipogenic acetyl-CoA pool labelling degree upon ACLY knockdown that is hidden in the bulk analysis and its effect on synthesis of individual fatty acids. Next, we adapted 13C-SpaceM to analyze tissue sections of mice harboring isocitrate dehydrogenase (IDH)-mutant gliomas. We found a strong induction of de novo fatty acid synthesis in the tumor tissue compared to the surrounding brain. Comparison of fatty acid isotopologue patterns revealed elevated uptake of mono-unsaturated and essential fatty acids in the tumor. Furthermore, our analysis uncovered substantial spatial heterogeneity in the labelling of the lipogenic acetyl-CoA pool indicative of metabolic reprogramming during microenvironmental adaptation. Overall, 13C-SpaceM enables novel ways for spatial probing of metabolic activity at the single cell level. Additionally, this methodology provides unprecedented insight into fatty acid uptake, synthesis and modification in normal and cancerous tissues.

Multiomics Characterization of a Less Invasive Microfluidic-Based Cell Sorting Technique.

Fluorescence-activated cell sorting (FACS) is a specialized technique to isolate specific cell subpopulations with a high level of recovery and accuracy. However, the cell sorting procedure can impact the viability and metabolic state of cells. Here, we performed a comparative study and evaluated the impact of traditional high-pressure charged droplet-based and microfluidic chip-based sorting on the metabolic and phosphoproteomic profile of different cell types. While microfluidic chip-based sorted cells more closely resembled the unsorted control group for most cell types tested, the droplet-based sorted cells showed significant metabolic and phosphoproteomic alterations. In particular, greater changes in redox and energy status were present in cells sorted with the droplet-based cell sorter along with larger shifts in proteostasis. 13C-isotope tracing analysis on cells recovering postsorting revealed that the sorter-induced suppression of mitochondrial TCA cycle activity recovered faster in the microfluidic chip-based sorted group. Apart from this, amino acid and lipid biosynthesis pathways were suppressed in sorted cells, with minimum impact and faster recovery in the microfluidic chip-based sorted group. These results indicate microfluidic chip-based sorting has a minimum impact on metabolism and is less disruptive compared to droplet-based sorting.