Labeling Of Metabolites Research Articles

Divergent downstream biosynthetic pathways are supported by L-cysteine synthases of Mycobacterium tuberculosis.

Mycobacterium tuberculosis's (Mtb) autarkic lifestyle within the host involves rewiring its transcriptional networks to combat host-induced stresses. With the help of RNA sequencing performed under various stress conditions, we identified that genes belonging to Mtb sulfur metabolism pathways are significantly upregulated during oxidative stress. Using an integrated approach of microbial genetics, transcriptomics, metabolomics, animal experiments, chemical inhibition, and rescue studies, we investigated the biological role of non-canonical L-cysteine synthases, CysM and CysK2. While transcriptome signatures of RvΔcysM and RvΔcysK2 appear similar under regular growth conditions, we observed unique transcriptional signatures when subjected to oxidative stress. We followed pool size and labelling (34S) of key downstream metabolites, viz. mycothiol and ergothioneine, to monitor L-cysteine biosynthesis and utilization. This revealed the significant role of distinct L-cysteine biosynthetic routes on redox stress and homeostasis. CysM and CysK2 independently facilitate Mtb survival by alleviating host-induced redox stress, suggesting they are not fully redundant during infection. With the help of genetic mutants and chemical inhibitors, we show that CysM and CysK2 serve as unique, attractive targets for adjunct therapy to combat mycobacterial infection.

An Organism-Level Quantitative Flux Model of Energy Metabolism in Mice.

A flux model of energy metabolism integrating 13 C labeling of metabolites and CO 2 Circulating nutrients have characteristic partition between oxidation and storageCirculating nutrients' total cycling flux outweighs their total oxidation fluxCycling fluxes are extensively elevated in ob/ob but not in diet-induced obese mice.

Abstract IA016: Metabolic reprogramming and cancer progression in patients

Abstract IA016: Metabolic reprogramming and cancer progression in patients

Steady Laminar Flow Decreases Endothelial Glycolytic Flux While Enhancing Proteoglycan Synthesis and Antioxidant Pathways.

Endothelial cells in steady laminar flow assume a healthy, quiescent phenotype, while endothelial cells in oscillating disturbed flow become dysfunctional. Since endothelial dysfunction leads to atherosclerosis and cardiovascular disease, it is important to understand the mechanisms by which endothelial cells change their function in varied flow environments. Endothelial metabolism has recently been proven a powerful tool to regulate vascular function. Endothelial cells generate most of their energy from glycolysis, and steady laminar flow may reduce endothelial glycolytic flux. We hypothesized that steady laminar but not oscillating disturbed flow would reduce glycolytic flux and alter glycolytic side branch pathways. In this study, we exposed human umbilical vein endothelial cells to static culture, steady laminar flow (20 dynes/cm2 shear stress), or oscillating disturbed flow (4 ± 6 dynes/cm2 shear stress) for 24 h using a cone-and-plate device. We then measured glucose and lactate uptake and secretion, respectively, and glycolytic metabolites. Finally, we explored changes in the expression and protein levels of endothelial glycolytic enzymes. Our data show that endothelial cells in steady laminar flow had decreased glucose uptake and 13C labeling of glycolytic metabolites while cells in oscillating disturbed flow did not. Steady laminar flow did not significantly change glycolytic enzyme gene or protein expression, suggesting that glycolysis may be altered through enzyme activity. Flow also modulated glycolytic side branch pathways involved in proteoglycan and glycosaminoglycan synthesis, as well as oxidative stress. These flow-induced changes in endothelial glucose metabolism may impact the atheroprone endothelial phenotype in oscillating disturbed flow.

Metabolic signatures of thymomas: potential biomarkers and treatment targets.

A study of tumour metabolic reprogramming has revealed disease biomarkers and avenues for therapeutic intervention. Metabolic reprogramming in thymoma is currently understudied and largely unknown. This study utilized metabolomics and isotope tracing with 13C-glucose to metabolically investigate thymomas, adjacent thymic tissue and benign thymic lesions. From 2017 to 2021, 20 patients with a suspected thymoma were recruited to this prospective Institutional Review Board approved clinical trial. At the time of surgery, 11 patients were infused with 13C-glucose, a stable, non-radioactive tracer which reports the flow of carbon through metabolic pathways. Samples were analysed by mass spectrometry to measure the abundance of >200 metabolites.13C enrichment was measured in patients who received 13C-glucose infusions. Histological analysis showed that 9 patients had thymomas of diverse subtypes and 11 patients had benign cysts. In our metabolomic analysis, thymomas could be distinguished from both adjacent thymus tissue and benign lesions by metabolite abundances. Metabolites in pyrimidine biosynthesis and glycerophospholipid metabolism were differentially expressed across these tissues.13C-glucose infusions revealed differential labelling patterns in thymoma compared to benign cysts and normal thymus tissue. The lactate/3PG labelling ratio, a metabolic marker in aggressive lung tumours correlated with lactate uptake, was increased in thymomas (1.579) compared to normal thymus (0.945) and benign masses (0.807) (thymic tissue versus tumour P = 0.021, tumour versus benign P = 0.013). We report metabolic biomarkers, including differential 13C labelling of metabolites from central metabolism, that distinguish thymomas from benign tissues. Altered glucose and lactate metabolism warrant further investigation and may provide novel therapeutic targets for thymoma.

GEN-Click: Genetically Encodable Click Reactions for Spatially Restricted Metabolite Labeling.

Chemical reactions for the in situ modification of biomolecules within living cells are under development. Among these reactions, bio-orthogonal reactions such as click chemistry using copper(I) and Staudinger ligation are widely used for specific biomolecule tracking in live systems. However, currently available live cell copper(I)-catalyzed azide/alkyne cycloaddition reactions are not designed in a spatially resolved manner. Therefore, we developed the "GEN-Click" system, which can target the copper(I)-catalyzed azide/alkyne cycloaddition reaction catalysts proximal to the protein of interest and can be genetically expressed in a live cell. The genetically controlled, spatially restricted, metal-catalyzed biorthogonal reaction can be used for proximity biotin labeling of various azido-bearing biomolecules (e.g., protein, phospholipid, oligosaccharides) in living cell systems. Using GEN-Click, we successfully detected local metabolite-transferring events at cell-cell contact sites.

In vivo assessment of β-hydroxybutyrate metabolism in mouse brain using deuterium (2 H) MRS.

To monitor the metabolic turnover of β-hydroxybutyrate (BHB) oxidation using 2 H-MRS in conjunction with intravenous administration of 2 H labeled BHB. Nine-month-old mice were infused with [3,4,4,4]-2 H4 -BHB (d4 -BHB; 3.11 g/kg) through the tail vein using a bolus variable infusion rate for a period of 90 min. The labeling of downstream cerebral metabolites from the oxidative metabolism of d4 -BHB was monitored using 2 H-MRS spectra acquired with a home-built 2 H surface coil on a 9.4T preclinical MR scanner with a temporal resolution of 6.25 min. An exponential model was fit to the BHB and glutamate/glutamine (Glx) turnover curves to determine rate constants of metabolite turnover and to aid in the visualization of metabolite time courses. Deuterium label was incorporated into Glx from BHB metabolism through the tricarboxylic acid (TCA) cycle, with an increase in the level of [4,4]-2 H2 -Glx (d2 -Glx) over time and reaching a quasi-steady state concentration of ∼0.6± 0.1 mM following 30 min of infusion. Complete oxidative metabolic breakdown of d4 -BHB also resulted in the formation of semi-heavy water (HDO), with a four-fold (10.1 to ∼42.1± 7.3 mM) linear (R2 = 0.998) increase in its concentration by the end of infusion. The rate constant of Glx turnover from d4 -BHB metabolism was determined to be 0.034 ± 0.004 min-1 . 2 H-MRS can be used to monitor the cerebral metabolism of BHB with its deuterated form by measuring the downstream labeling of Glx. The integration of 2 H-MRS with deuterated BHB substrate provides an alternative and clinically promising MRS tool to detect neurometabolic fluxes in healthy and disease conditions.

Immune checkpoint inhibition: a future guided by radiology.

The limitation of the function of antitumour immune cells is a common hallmark of cancers that enables their survival. As such, the potential of immune checkpoint inhibition (ICI) acts as a paradigm shift in the treatment of a range of cancers but has not yet been fully capitalised. Combining minimally and non-invasive locoregional therapies offered by radiologists with ICI is now an active field of research with the aim of furthering therapeutic capabilities in medical oncology. In parallel to this impending advancement, the "imaging toolbox" available to radiologists is also growing, enabling more refined tumour characterisation as well as greater accuracy in evaluating responses to therapy. Options range from metabolite labelling to cellular localisation to immune checkpoint screening. It is foreseeable that these novel imaging techniques will be integrated into personalised treatment algorithms. This growth in the field must include updating the current standardised imaging criteria to ensure they are fit for purpose. Such criteria is crucial to both appropriately guide clinical decision-making regarding next steps of treatment, but also provide reliable prognosis. Quantitative approaches to these novel imaging techniques are also already being investigated to further optimise personalised therapeutic decision-making. The therapeutic potential of specific ICIs and locoregional therapies could be determined before administration thus limiting unnecessary side-effects whilst maintaining efficacy. Several radiological aspects of oncological care are advancing simultaneously. Therefore, it is essential that each development is assessed for clinical use and optimised to ensure the best treatment decisions are being offered to the patient. In this review, we discuss state of the art advances in novel functional imaging techniques in the field of immuno-oncology both pre-clinically and clinically.

Breast cancer cells that preferentially metastasize to lung or bone are more glycolytic, synthesize serine at greater rates, and consume less ATP and NADPH than parent MDA-MB-231 cells

Gene expression signatures associated with breast cancer metastases suggest that metabolic re-wiring is important for metastatic growth in lungs, bones, and other organs. However, since pathway fluxes depend on additional factors such as ATP demand, allosteric effects, and post-translational modification, flux analysis is necessary to conclusively establish phenotypes. In this study, the metabolic phenotypes of breast cancer cell lines with low (T47D) or high (MDA-MB-231) metastatic potential, as well as lung (LM)- and bone (BoM)-homing lines derived from MDA-MB-231 cells, were assessed by 13C metabolite labeling from [1,2-13C] glucose or [5-13C] glutamine and the rates of nutrient and oxygen consumption and lactate production. MDA-MB-231 and T47D cells produced 55 and 63%, respectively, of ATP from oxidative phosphorylation, whereas LM and BoM cells were more glycolytic, deriving only 20–25% of their ATP from mitochondria. ATP demand by BoM and LM cells was approximately half the rate of the parent cells. Of the anabolic fluxes assessed, nucleotide synthesis was the major ATP consumer for all cell lines. Glycolytic NADH production by LM cells exceeded the rate at which it could be oxidized by mitochondria, suggesting that the malate-aspartate shuttle was not involved in re-oxidation of these reducing equivalents. Serine synthesis was undetectable in MDA-MB-231 cells, whereas 3–5% of glucose was shunted to serine by LM and BoM lines. Proliferation rates of T47D, BoM, and LM lines tightly correlated with their respiration-normalized NADPH production rates. In contrast, MDA-MB-231 cells produced NADPH and GSH at higher rates, suggesting this line is more oxidatively stressed. Approximately half to two-thirds of NADPH produced by T47D, MDA-MB-231, and BoM cells was from the oxidative PPP, whereas the majority in LM cells was from the folate cycle. All four cell lines used the non-oxidative PPP to produce pentose phosphates, although this was most prominent for LM cells. Taken together, the metabolic phenotypes of LM and BoM lines differed from the parent line and from each other, supporting the metabolic re-wiring hypothesis as a feature of metastasis to lung and bone.

Unravelling metabolic cross‐feeding in a yeast–bacteria community using 13C‐based proteomics

Cross‐feeding is fundamental to the diversity and function of microbial communities. However, identification of cross‐fed metabolites is often challenging due to the universality of metabolic and biosynthetic intermediates. Here, we use 13C isotope tracing in peptides to elucidate cross‐fed metabolites in co‐cultures of Saccharomyces cerevisiae and Lactococcus lactis. The community was grown on lactose as the main carbon source with either glucose or galactose fraction of the molecule labelled with 13C. Data analysis allowing for the possible mass‐shifts yielded hundreds of peptides for which we could assign both species identity and labelling degree. The labelling pattern showed that the yeast utilized galactose and, to a lesser extent, lactic acid shared by L. lactis as carbon sources. While the yeast provided essential amino acids to the bacterium as expected, the data also uncovered a complex pattern of amino acid exchange. The identity of the cross‐fed metabolites was further supported by metabolite labelling in the co‐culture supernatant, and by diminished fitness of a galactose‐negative yeast mutant in the community. Together, our results demonstrate the utility of 13C‐based proteomics for uncovering microbial interactions.

Engineering and adaptive laboratory evolution of Escherichia coli for improving methanol utilization based on a hybrid methanol assimilation pathway.

Engineering Escherichia coli for efficient methanol assimilation is important for developing methanol as an emerging next-generation feedstock for industrial biotechnology. While recent attempts to engineer E. coli as a synthetic methylotroph have achieved great success, most of these works are based on the engineering of the prokaryotic ribulose monophosphate (RuMP) pathway. In this study, we introduced a hybrid methanol assimilation pathway which consists of prokaryotic methanol dehydrogenase (Mdh) and eukaryotic xylulose monophosphate (XuMP) pathway enzyme dihydroxyacetone synthase (Das) into E. coli and reprogrammed E. coli metabolism to improve methanol assimilation by combining rational design and adaptive laboratory evolution. By deletion and down-regulation of key genes in the TCA cycle and glycolysis to increase the flux toward the cyclic XuMP pathway, methanol consumption and the assimilation of methanol to biomass were significantly improved. Further improvements in methanol utilization and cell growth were achieved via adaptive laboratory evolution and a final evolved strain can grow on methanol with only 0.1g/L yeast extract as co-substrate. 13C-methanol labeling assay demonstrated significantly higher labeling in intracellular metabolites in glycolysis, TCA cycle, pentose phosphate pathway, and amino acids. Transcriptomics analysis showed that the expression of fba, dhak, and part of pentose phosphate pathway genes were highly up-regulated, suggesting that the rational engineering strategies and adaptive evolution are effective for activating the cyclic XuMP pathway. This study demonstrated the feasibility and provided new strategies to construct synthetic methylotrophy of E. coli based on the hybrid methanol assimilation pathway with Mdh and Das.

Tracing Carbon Metabolism with Stable Isotope Metabolomics Reveals the Legacy of Diverse Carbon Sources in Soil.

Tracking the metabolic activity of whole soil communities can improve our understanding of the transformation and fate of carbon in soils. We used stable isotope metabolomics to trace 13C from nine labeled carbon sources into the water-soluble metabolite pool of an agricultural soil over time. Soil was amended with a mixture of all nine sources, with one source isotopically labeled in each treatment. We compared changes in the 13C enrichment of metabolites with respect to carbon source and time over a 48-day incubation and contrasted differences between soluble sources (glucose, xylose, amino acids, etc.) and insoluble sources (cellulose and palmitic acid). Whole soil metabolite profiles varied singularly by time, while the composition of 13C-labeled metabolites differed primarily by carbon source (R2 = 0.68) rather than time (R2 = 0.07), with source-specific differences persisting throughout incubations. The 13C labeling of metabolites from insoluble carbon sources occurred slower than that from soluble sources but yielded a higher average atom percent (atom%) 13C in metabolite markers of biomass (amino acids and nucleic acids). The 13C enrichment of metabolite markers of biomass stabilized between 5 and 15 atom% 13C by the end of incubations. Temporal patterns in the 13C enrichment of tricarboxylic acid cycle intermediates, nucleobases (uracil and thymine), and by-products of DNA salvage (allantoin) closely tracked microbial activity. Our results demonstrate that metabolite production in soils is driven by the carbon source supplied to the community and that the fate of carbon in metabolites do not generally converge over time as a result of ongoing microbial processing and recycling. IMPORTANCE Carbon metabolism in soil remains poorly described due to the inherent difficulty of obtaining information on the microbial metabolites produced by complex soil communities. Our study demonstrates the use of stable isotope probing (SIP) to study carbon metabolism in soil by tracking 13C from supplied carbon sources into metabolite pools and biomass. We show that differences in the metabolism of sources influence the fate of carbon in soils. Heterogeneity in 13C-labeled metabolite profiles corresponded with compositional differences in the metabolically active populations, providing a basis for how microbial community composition correlates with the quality of soil carbon. Our study demonstrates the application of SIP-metabolomics in studying soils and identifies several metabolite markers of growth, activity, and other aspects of microbial function.

Estradiol, Estrone and Ethinyl Estradiol Metabolism Studied by High Resolution LC-MS/MS Using Stable Isotope Labeling and Trapping of Reactive Metabolites.

Biotransformation reactions that xenobiotics undergo during their metabolism are crucial for their proper excretion from the body, but can also be a source of toxicity, especially in the case of reactive metabolite formation. Unstable, reactive metabolites are capable of covalent binding to proteins, and have often been linked to liver damage and other undesired side effects. A common technique to assess the formation of reactive metabolites employs trapping them in vitro with glutathione and characterizing the resulting adducts by liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS). Some endogenous compounds, however, can interfere with xenobiotic metabolites of interest, making the analysis more difficult. This study demonstrates the usefulness of isotope-labeled compounds to detect and elucidate the structures of both stable metabolites and trapped adducts of three estrogen analogs using an untargeted LC-MS/MS workflow. The metabolism of estradiol, estrone and ethinyl estradiol was investigated. Unlabeled and deuterated versions of these three compounds were incubated with human or rat liver microsomes in the presence of two different trapping agents, namely glutathione and N-acetylcysteine. The detection of closely eluting deuterated peaks allowed us to confirm the formation of several known metabolites, as well as many previously uncharacterized ones. The structure of each adduct was elucidated by the detailed analysis of high-resolution MS/MS spectra for elucidating fragmentation pathways with accurate mass measurements. The use of isotopic labeling was crucial in helping confirm many metabolites and adduct structures, as well as removing endogenous interferences.

Lactate is an epigenetic metabolite that drives survival in model systems of glioblastoma

Lactate accumulates to a significant amount in glioblastomas (GBMs), the most common primary malignant brain tumor with an unfavorable prognosis. However, it remains unclear whether lactate is metabolized by GBMs. Here, we demonstrated that lactate rescued patient-derived xenograft (PDX) GBM cells from nutrient-deprivation-mediated cell death. Transcriptome analysis, ATAC-seq, and ChIP-seq showed that lactate entertained a signature of oxidative energy metabolism. LC/MS analysis demonstrated that U-13C-lactate elicited substantial labeling of TCA-cycle metabolites, acetyl-CoA, and histone protein acetyl-residues in GBM cells. Lactate enhanced chromatin accessibility and histone acetylation in a manner dependent on oxidative energy metabolism and the ATP-citrate lyase (ACLY). Utilizing orthotopic PDX models of GBM, a combined tracer experiment unraveled that lactate carbons were substantially labeling the TCA-cycle metabolites. Finally, pharmacological blockage of oxidative energy metabolism extended overall survival in two orthotopic PDX models in mice. These results establish lactate metabolism as a novel druggable pathway for GBM.

Tirzepatide induces a thermogenic-like amino acid signature in brown adipose tissue

ObjectivesTirzepatide, a dual GIP and GLP-1 receptor agonist, delivered superior glycemic control and weight loss compared to selective GLP-1 receptor (GLP-1R) agonism in patients with type 2 diabetes (T2D). These results have fueled mechanistic studies focused on understanding how tirzepatide achieves its therapeutic efficacy. Recently, we found that treatment with tirzepatide improves insulin sensitivity in humans with T2D and obese mice in concert with a reduction in circulating levels of branched-chain amino (BCAAs) and keto (BCKAs) acids, metabolites associated with development of systemic insulin resistance (IR) and T2D. Importantly, these systemic effects were found to be coupled to increased expression of BCAA catabolic genes in thermogenic brown adipose tissue (BAT) in mice. These findings led us to hypothesize that tirzepatide may lower circulating BCAAs/BCKAs by promoting their catabolism in BAT. MethodsTo address this question, we utilized a murine model of diet-induced obesity and employed stable-isotope tracer studies in combination with metabolomic analyses in BAT and other tissues. ResultsTreatment with tirzepatide stimulated catabolism of BCAAs/BCKAs in BAT, as demonstrated by increased labeling of BCKA-derived metabolites, and increases in levels of byproducts of BCAA breakdown, including glutamate, alanine, and 3-hydroxyisobutyric acid (3-HIB). Further, chronic administration of tirzepatide increased levels of multiple amino acids in BAT that have previously been shown to be elevated in response to cold exposure. Finally, chronic treatment with tirzepatide led to a substantial increase in several TCA cycle intermediates (α-ketoglutarate, fumarate, and malate) in BAT. ConclusionsThese findings suggest that tirzepatide induces a thermogenic-like amino acid profile in BAT, an effect that may account for reduced systemic levels of BCAAs in obese IR mice.

An automated workflow that generates atom mappings for large-scale metabolic models and its application to Arabidopsis thaliana.

Quantification of reaction fluxes of metabolic networks can help us understand how the integration of different metabolic pathways determines cellular functions. Yet, intracellular fluxes cannot be measured directly but are estimated with metabolic flux analysis (MFA), which relies on the patterns of isotope labeling of metabolites in the network. The application of MFA also requires a stoichiometric model with atom mappings that are currently not available for the majority of large-scale metabolic network models, particularly of plants. While automated approaches such as the Reaction Decoder Toolkit (RDT) can produce atom mappings for individual reactions, tracing the flow of individual atoms of the entire reactions across a metabolic model remains challenging. Here we establish an automated workflow to obtain reliable atom mappings for large-scale metabolic models by refining the outcome of RDT, and apply the workflow to metabolic models of Arabidopsis thaliana. We demonstrate the accuracy of RDT through a comparative analysis with atom mappings from a large database of biochemical reactions, MetaCyc. We further show the utility of our automated workflow by simulating 15 N isotope enrichment and identifying nitrogen (N)-containing metabolites which show enrichment patterns that are informative for flux estimation in future 15 N-MFA studies of A. thaliana. The automated workflow established in this study can be readily expanded to other species for which metabolic models have been established and the resulting atom mappings will facilitate MFA and graph-theoretic structural analyses with large-scale metabolic networks.

Synergistic Effect of β-Lapachone and Aminooxyacetic Acid on Central Metabolism in Breast Cancer.

The compound β-lapachone, a naturally derived naphthoquinone, has been utilized as a potent medicinal nutrient to improve health. Over the last twelve years, numerous reports have demonstrated distinct associations of β-lapachone and NAD(P)H: quinone oxidoreductase 1 (NQO1) protein in the amelioration of various diseases. Comprehensive research of NQO1 bioactivity has clearly confirmed the tumoricidal effects of β-lapachone action through NAD+-keresis, in which severe DNA damage from reactive oxygen species (ROS) production triggers a poly-ADP-ribose polymerase-I (PARP1) hyperactivation cascade, culminating in NAD+/ATP depletion. Here, we report a novel combination strategy with aminooxyacetic acid (AOA), an aspartate aminotransferase inhibitor that blocks the malate-aspartate shuttle (MAS) and synergistically enhances the efficacy of β-lapachone metabolic perturbation in NQO1+ breast cancer. We evaluated metabolic turnover in MDA-MB-231 NQO1+, MDA-MB-231 NQO1−, MDA-MB-468, and T47D cancer cells by measuring the isotopic labeling of metabolites from a [U-13C]glucose tracer. We show that β-lapachone treatment significantly hampers lactate secretion by ~85% in NQO1+ cells. Our data demonstrate that combinatorial treatment decreases citrate, glutamate, and succinate enrichment by ~14%, ~50%, and ~65%, respectively. Differences in citrate, glutamate, and succinate fractional enrichments indicate synergistic effects on central metabolism based on the coefficient of drug interaction. Metabolic modeling suggests that increased glutamine anaplerosis is protective in the case of MAS inhibition.

Development of a High-Coverage Quantitative Metabolome Analysis Method Using Four-Channel Chemical Isotope Labeling LC-MS for Analyzing High-Salt Fermented Food.

Metabolome analysis of high-salt fermented food can be an analytical challenge, as the salts can interfere with the sample processing and analysis. In this work, we describe a four-channel chemical isotope labeling (CIL) LC-MS approach for a comprehensive metabolome analysis of high-salt fermented food. The workflow includes metabolite extraction, chemical labeling of metabolites using dansyl chloride, dansylhydrazine, or p-dimethylaminophenacyl bromide reagents to enhance separation and ionization, LC-UV measurement of the total concentration of dansyl-labeled metabolites in each sample for sample normalization, mixing of 13C- and 12C-reagent-labeled samples, high-resolution LC-MS analysis, and data processing. Metabolome analysis of fermented foods, including fermented red pepper (FRP) sauce, soy sauce, and sufu (a fermented soybean food), showed unprecedented high metabolic coverage. Metabolome comparison of FRP, soy sauce, and sufu, as well as soy sauce and sufu, indicated great diversity of metabolite types and abundances in these foods. In addition, we analyzed two groups of samples of the same type, FRP with 10% (w/w) and 15% (w/w) salt contents, and detected large variations in multiple categories of metabolites belonging to a number of different metabolic pathways. We envisage that this CIL LC-MS approach can be generally used for metabolomic studies of high-salt fermented food. CIL LC-MS allows high-coverage identification and quantification that could not be done using other methods.

Imaging Glioblastoma Metabolism by Using Hyperpolarized [1-13C]Pyruvate Demonstrates Heterogeneity in Lactate Labeling: A Proof of Principle Study.

PurposeTo evaluate glioblastoma (GBM) metabolism by using hyperpolarized carbon 13 (13C) MRI to monitor the exchange of the hyperpolarized 13C label between injected [1-13C]pyruvate and tumor lactate and bicarbonate.Materials and MethodsIn this prospective study, seven treatment-naive patients (age [mean ± SD], 60 years ± 11; five men) with GBM were imaged at 3 T by using a dual-tuned 13C–hydrogen 1 head coil. Hyperpolarized [1-13C]pyruvate was injected, and signal was acquired by using a dynamic MRI spiral sequence. Metabolism was assessed within the tumor, in the normal-appearing brain parenchyma (NABP), and in healthy volunteers by using paired or unpaired t tests and a Wilcoxon signed rank test. The Spearman ρ correlation coefficient was used to correlate metabolite labeling with lactate dehydrogenase A (LDH-A) expression and some immunohistochemical markers. The Benjamini-Hochberg procedure was used to correct for multiple comparisons.ResultsThe bicarbonate-to-pyruvate (BP) ratio was lower in the tumor than in the contralateral NABP (P < .01). The tumor lactate-to-pyruvate (LP) ratio was not different from that in the NABP (P = .38). The LP and BP ratios in the NABP were higher than those observed previously in healthy volunteers (P < .05). Tumor lactate and bicarbonate signal intensities were strongly correlated with the pyruvate signal intensity (ρ = 0.92, P < .001, and ρ = 0.66, P < .001, respectively), and the LP ratio was weakly correlated with LDH-A expression in biopsy samples (ρ = 0.43, P = .04).ConclusionHyperpolarized 13C MRI demonstrated variation in lactate labeling in GBM, both within and between tumors. In contrast, bicarbonate labeling was consistently lower in tumors than in the surrounding NABP.Keywords: Hyperpolarized 13C MRI, Glioblastoma, Metabolism, Cancer, MRI, Neuro-oncology Supplemental material is available for this article. Published under a CC BY 4.0 license.

Metabolite-based cell sorting workflow for identifying microbes producing carbonyls in tobacco leaves.

Carbonyl compounds represented by aldehydes and ketones make an important contribution to the flavor of tobacco. Since most carbonyl compounds are produced by microbes during tobacco fermentation, identifying their producers is important to improve the quality of tobacco. Here, we created an efficient workflow that combines metabolite labeling with fluorescence-activated cell sorting (ML-FACS), 16S rRNA gene sequencing, and microbial culture to identify the microbes that produce aldehydes or ketones in fermented cigar tobacco leaves (FCTL). Microbes were labeled with a specific fluorescent dye (cyanine5 hydrazide) and separated by flow cytometry. Subsequently, the sorted microbes were identified and cultured under laboratory conditions. Four genera, Acinetobacter, Sphingomonas, Solibacillus, and Lysinibacillus, were identified as the main carbonyl compound-producing microbes in FCTL. In addition, these microorganisms could produce flavor-related aldehydes and ketones in a simple synthetic medium, such as benzaldehyde, phenylacetaldehyde, 4-hydroxy-3-ethoxy-benzaldehyde, and 3,5,5-trimethyl-2-cyclohexene-1-one. On the whole, this research has developed a new method to quickly isolate and identify microorganisms that produce aldehydes or ketones from complex microbial communities. ML-FACS would also be used to identify other compound-producing microorganisms in other systems. KEY POINTS: • An approach was developed to identify target microbes in complex communities. • Microbes that produce aldehyde/ketone flavor compounds in fermented cigar tobacco leaves were identified. • Functional microbes that produce aldehyde/ketone flavor compounds from the native environment were captured in pure cultures.