Metabolite Extraction Protocol Research Articles

Red blood cell metabolomics identify ergothioneine as a key metabolite in DMARD-naïve rheumatoid arthritis and response to methotrexate

Using a new red blood cell (RBC) metabolite extraction protocol, we performed a metabolomic analysis on RBCs in rheumatoid arthritis (RA) patients treated or not with methotrexate (MTX), with the two following objectives: to compare the RBC metabolic profiles of MTX-naïve RA patients and healthy controls (HC), and to investigate whether RBC profiles before and after MTX treatment in RA differed between responders and non-responders. Plasma analysis was performed in parallel. Metabolites were extracted and identified in RBCs and plasma by liquid chromatography-mass spectrometry. We compared the metabolomic fingerprints of 31 DMARD-naïve RA patients and 39 HCs. We also compared the RBC and plasma metabolomes of 25 RA patients who responded or not to MTX therapy before (M0) and after a 3-month treatment period (M3). Significance was determined by Storey’s false discovery rate (FDR) q-values to correct for multiple testing. RA patients and HCs differed in the metabolomic signature of RBCs. The signature mainly contained amino acids (AA). Eleven metabolites, including 4 metabolites belonging to the carbohydrate subclass and 2 amino acids (creatine and valine) showed accumulation in RBCs from RA patients. Conversely, citrulline (fold change = 0.83; q = 0.025), histidine (fold change = 0.86; q = 0.014) and ergothioneine (EGT) (fold change = 0.66; q = 0.024), were lower in RBC of RA patients. Five plasma metabolites, including succinic acid and hydroxyproline, were higher in RA patients, and 7 metabolites, including DHEA sulfate, alanine, threonine and ornithine, were lower. Among RA patients undergoing MTX treatment pre-treatment (M0), EGT values were significantly lower in non-responders. In conclusion, low RBC levels of EGT, a food-derived AA barely detectable in plasma, characterize DMARD naïve RA patients and lack of response to MTX treatment.

Carnitine O-octanoyltransferase (CROT) deficiency in mice leads to an increase of omega-3 fatty acids.

Introduction: Carnitine O-octanoyltransferase (CROT) is a well-established peroxisomal enzyme involved in liver fatty acid oxidation, but less is known about its recently discovered role in promoting vascular calcification, and whether CROT-dependent liver metabolism contributes to the latter. To date, CROT function in the context of calcification potential has been conducted in the dyslipidemic low-density lipoprotein receptor-deficient (Ldlr-/-) mice. Objectives: To differentiate peroxisome and CROT-dependent lipid biology from that of lipoprotein-mediated lipid biology, we therefore conducted a metabolomic analysis of the liver and plasma of normolipidemic CROT-deficient (Crot-/-) mice. Methods: We performed LC-MS-based metabolomics on liver and plasma derived from Crot-/- and Crot +/- mice and sibling Crot+/+ mice, using a dual-phase metabolite extraction protocol, and multiple LC-MS acquisition strategies. Results: We identified between 79 to 453 annotated metabolites from annotated metabolites from liver samples, and 117 to 424 annotated metabolites from plasma samples. Through differential abundance analysis, we determined that omega-3 fatty acids such as EPA, DPA, and DHA were higher in the liver of Crot-/- and Crot +/- mice than Crot+/+ mice. EPA were higher in plasma of Crot-/- mice than Crot+/+ mice. We also determined that the anti-inflammatory dicarboxylic acids, tetradecanedioic acid and azelaic acid, were higher in the plasma of CROT-deficient mice. Conclusion: Our study associated genetic CROT deletion with increased levels of anti-inflammatory molecules in mouse liver and plasma. These results suggest a potential mechanism for anti-calcification effects of CROT suppression and the potential use of omega-3 fatty acids as biomarkers for future CROT inhibition therapies.

Enhanced molecular release from elderly bone samples using collagenase I: insights into fatty acid metabolism alterations

BackgroundBone is a metabolically active tissue containing different cell types acting as endocrine targets and effectors. Further, bone is a dynamic depot for calcium, phosphorous and other essential minerals. The tissue matrix is subjected to a constant turnover in response to mechanical/endocrine stimuli. Bone turnover demands high energy levels, making fatty acids a crucial source for the bone cells. However, the current understanding of bone cell metabolism is poor. This is partly due to bone matrix complexity and difficulty in small molecules extraction from bone samples. This study aimed to evaluate the effect of metabolite sequestering from a protein-dominated matrix to increase the quality and amount of metabolomics data in discovering small molecule patterns in pathological conditions.MethodsHuman bone samples were collected from 65 to 85 years old (the elderly age span) patients who underwent hip replacement surgery. Separated cortical and trabecular bone powders were treated with decalcifying, enzymatic (collagenase I and proteinase K) and solvent-based metabolite extraction protocols. The extracted mixtures were analyzed with the high-resolution mass spectrometry (HRMS). Data analysis was performed with XCMS and MetaboAnalystR packages.ResultsFast enzymatic treatment of bone samples before solvent addition led to a significantly higher yield of metabolite extraction. Collagenase I and proteinase K rapid digestion showed more effectiveness in cortical and trabecular bone samples, with a significantly higher rate (2.2 folds) for collagenase I. Further analysis showed significant enrichment in pathways like de novo fatty acid biosynthesis, glycosphingolipid metabolism and fatty acid oxidation-peroxisome.ConclusionThis work presents a novel approach for bone sample preparation for HRMS metabolomics. The disruption of bone matrix conformation at the molecular level helps the molecular release into the extracting solvent and, therefore, can lead to higher quality results and trustable biomarker discovery. Our results showed β-oxidation alteration in the aged bone sample. Future work covering more patients is worthy to identify the effective therapeutics to achieve healthy aging.

Comparison of freeze-thaw and sonication cycle-based methods for extracting AMR-associated metabolites from Staphylococcus aureus.

Emerging antimicrobial resistance (AMR) among Gram-positive pathogens, specifically in Staphylococcus aureus (S. aureus), is becoming a leading public health concern demanding effective therapeutics. Metabolite modulation can improve the efficacy of existing antibiotics and facilitate the development of effective therapeutics. However, it remained unexplored for drug-resistant S. aureus (gentamicin and methicillin-resistant), primarily due to the dearth of optimal metabolite extraction protocols including a protocol for AMR-associated metabolites. Therefore, in this investigation, we have compared the performance of the two most widely used methods, i.e., freeze-thaw cycle (FTC) and sonication cycle (SC), alone and in combination (FTC + SC), and identified the optimal method for this purpose. A total of 116, 119, and 99 metabolites were identified using the FTC, SC, and FTC + SC methods, respectively, leading to the identification of 163 metabolites cumulatively. Out of 163, 69 metabolites were found to be associated with AMR in published literature consisting of the highest number of metabolites identified by FTC (57) followed by SC (54) and FTC + SC (40). Thus, the performances of FTC and SC methods were comparable with no additional benefits of combining both. Moreover, each method showed biasness toward specific metabolite(s) or class of metabolites, suggesting that the choice of metabolite extraction method shall be decided based on the metabolites of interest in the investigation.

Whole Body Distribution of Labile Coenzymes and Antioxidants in a Mouse Model as Visualized Using 1H NMR Spectroscopy.

Coenzyme A, acetyl coenzyme A, coenzymes of cellular energy, coenzymes of redox reactions, and antioxidants mediate biochemical reactions fundamental to the functioning of all living cells. There is an immense interest in measuring them routinely in biological specimens to gain insights into their roles in cellular functions and to help characterize the biological status. However, it is challenging to measure them ex vivo as they are sensitive to specimen harvesting, extraction, and measurement conditions. This challenge is largely underappreciated and carries the risk of grossly inaccurate measurements that lead to incorrect inferences. To date, several efforts have been focused on alleviating this challenge using NMR spectroscopy. However, a comprehensive solution for the measurement of the compounds in a wide variety of biological specimens is still lacking. As a part of addressing this challenge, we demonstrate here that the total pool of each group of unstable metabolites offers a starting place for the representation of labile metabolites in biological specimens. Based on this approach, in this proof-of-concept study, we determine the distribution of the labile compounds in different organs including heart, kidney, liver, brain, and skeletal muscle of a mouse model. The results were independently validated using different specimens and a different metabolite extraction protocol. Further, we show that both stable and unstable metabolites were distributed differentially in different organs, which signifies their differential functional roles, the knowledge of which is currently lacking for many metabolites. Intriguingly, the concentration of taurine, an amino sulfonic acid, in skeletal muscle is >30 mM, which is the highest for any metabolite in a mammalian tissue known to date. To the best of our knowledge, this is the first study to profile the whole body distribution of the labile and other high-concentration metabolites using NMR spectroscopy. The results may pave ways for gaining new insights into cellular functions in health and diseases.

FT-ICR-MS-based metabolomics: A deep dive into plant metabolism.

Metabolomics involves the identification and quantification of metabolites to unravel the chemical footprints behind cellular regulatory processes and to decipher metabolic networks, opening new insights to understand the correlation between genes and metabolites. In plants, it is estimated the existence of hundreds of thousands of metabolites and the majority is still unknown. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) is a powerful analytical technique to tackle such challenges. The resolving power and sensitivity of this ultrahigh mass accuracy mass analyzer is such that a complex mixture, such as plant extracts, can be analyzed and thousands of metabolite signals can be detected simultaneously and distinguished based on the naturally abundant elemental isotopes. In this review, FT-ICR-MS-based plant metabolomics studies are described, emphasizing FT-ICR-MS increasing applications in plant science through targeted and untargeted approaches, allowing for a better understanding of plant development, responses to biotic and abiotic stresses, and the discovery of new natural nutraceutical compounds. Improved metabolite extraction protocols compatible with FT-ICR-MS, metabolite analysis methods and metabolite identification platforms are also explored as well as new in silico approaches. Most recent advances in MS imaging are also discussed.

Assessment of Biphasic Extraction Methods of Mouse Fecal Metabolites for Liquid Chromatography-Mass Spectrometry-Based Metabolomic Studies.

With the increasing knowledge about the important roles of gut microbiota on the biological system, a systematic strategy to profile the fecal metabolome is urgently needed. Thus, an unbiased, efficient, and reproducible fecal metabolite extraction protocol needs to be established; however, the effect of biphasic extraction methods for the fecal samples remains unclear. In this study, five different methods were assessed in the extraction of polar and non-polar metabolites for the liquid chromatography-mass spectrometry (LC-MS)-based mouse fecal metabolomic study. First, the detection coverage of two extraction systems, the Bligh and Dyer extraction method (M1, chloroform/methanol/water, 2/2/1.8) and Matyash method (M2, methyl tert-butyl ether (MTBE)/methanol/water, 10/3/2.5), was compared; then, MTBE/methanol/water system with different solvent ratios (M3, 2.6/2.0/2.4; M4, 4.5/1/2.5; and M5, 3/2.5/2.5) were further evaluated. The results showed that M2 showed higher detection coverage than M1. For the MTBE/methanol/water system with different solvent ratios, M3 showed the largest detection coverage based on peak numbers and numbers of putatively annotated metabolites, while M4 presented the least overlap between two phases, higher peak intensities of metabolites, and superior reproducibility. Based on the above evidence, M4 was recommended for the biphasic extraction of fecal metabolites in the LC-MS-based mouse fecal metabolomic study.

The Metabolomic Status of the Differentiating Myeloid Lineage in MDS with Low and High Bone Marrow Blast Counts

Despite its major role in cellular biology, metabolism has only recently acquired a principal role in the research of the most profound cellular cycle disturbance, cancerous transformation. Myelodysplastic syndromes (MDS), a massively heterogeneous group of Hematopoietic Stem/ Progenitor Cell (HSC/HPC) disorders lie at the interface of normal differentiation and malignant transformation and have thus drew great attention due to their polymorphic presentation and elusive pathophysiology. Failure to establish a direct etiopathogenic relationship with specific genetic aberrations, along with the novel finding of a highly deregulated HIF1 activity by several unrelated research groups worldwide, including ours, urged us to investigate the metabolomic status of human bone marrow derived differentiating myeloid lineage in comparison with one another as well as with control samples. BM aspiration samples collected from 14 previously untreated MDS patients (10 patients with <5% (1 SLD, 8MLD, 1del5q, group 1- G1) and 4 with >5% BM blasts (2 EB1, 2 EB2group 2 - G2)) and 5 age matched controls. Myeloid lineage cells were isolated through ficoll bilayer protocol. All samples contained homogenous myeloid lineage subpopulations, assessedthrough optical microscopy. Two different metabolite extraction protocols were applied. The one with the best metabolites yield (50% MeOH, 30% ACN, 20% H2O) was chosen. LC-MS/MS analysis was performed using UPLC 1290 system (Agilent Technologies) coupled to a TripleTOF 5600+ mass spectrometer (SCIEX) equipped with SWATH acquisition, SelexION technology and an electrospray ionization source (ESI). A threshold of a minimum of three samples expressing a given metabolite was set against data sparsity. Data tables were scaled by data centering and setting unit variance. Log2 Foldcalculation and PLS analysis were performed for the two datasets (positive and negative ion-modes). R2 and Q2 for positive ion-mode and negative-ion mode analyses were determined. Both datasets were merged in a unique data table by taking into account maximum absolute log2 foldvalues, when a metabolite was found in both datasets. Warburg effect was evidently present in both the G1 and G2 vs control comparisons, yet the role of this stem like aerobic glycolysis seems markedly different in the two groups. While in the G2 group it serves to rescue glucose from complete burn in the mitochondrion and thus shuts it towards nucleotide synthesis (Pentose Phosphate Pathway found upregulated) with the added benefit of increased reduced Glutathione synthesis and improved redox state, in the G1 group proves detrimental. This greatly variable effect of the same phenomenon in the cellular fate lies upon the quality and functionality of the cellular mitochondrial content. G2 precursors presented functional mitochondrial (decreased NAD/NADH and FAD/FADH2) contrary to the G1 ones (Table). Failing TCA cycle, with increased NAD/NADH and FAD/FADH2 ratios and markedly increased ADP/ATP levels leads to FAs accumulation due to failure of effective adequate β oxidation. The uncontrolled increase in the NAD/NADH ratio stimulates upper glycolysis into a turbo mode further increasing the ADP/ATP, depleting cellular energy contents, engaging it to a never-ending deadly metabolism. The enormous abundance of upper glycolytic intermediates is relieved through phospholipid and ceramide synthesis, all found massively upregulated in both the MDS vs control yet also in the G1 vs G2 comparisons. FAs, mostly phospholipid and ceramide accumulation, interrupt the mitochondrial membrane lipidome further incapacitating metabolic integrity and inducing their autophagic degradation which further stimulates the Warburg effect. This type of metabolic reprogramming is eventually targeted to epigenetic modifier production, increased S-adenosyl-methionine, the major methyl group donor, 2-HydroxyGlutarate, a potent epigenetic modifier and notorious oncometabolite, Acetyl-Lysine, the major acetyl- group donor, even glutathione. We therefore present a model of an uncontrolled Warburg effect which in the G1 group confers premature death of the hematopoietic precursors, the ineffective hematopoiesis of MDS. Yet, under the pressure of the vastly upregulated epigenetic modifiers cellular fate changes, the G1 precursors adapt and transform to the G2 ones yet eventually to Acute Myeloid Leukemia blasts. Table Disclosures Vassilopoulos: Genesis pharma SA: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees; Gilead: Research Funding; Abbvie: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees.

I have a kit and I create worlds: synthetic ecology from synthetic genomes

The genome is the blueprint for life. A genome sequence can be transcribed and translated by molecular machines to assemble an organism capable of replication, sensation, and response. Organisms respond to each other, forming intricate interaction webs that manifest as ecosystems, defining the world we live in and rely on. It all starts with a genome. And if we can build a genome, we can create worlds. This article is protected by copyright. All rights reserved.

Fast and ergonomic extraction of adherent mammalian cells for NMR-based metabolomics studies.

Cellular metabolomics has become key to elucidate mechanistic aspects in various fields such as cancerology or pharmacology, and is rapidly becoming a standard phenotyping tool accessible to the broad biological community. Acquisition of reliable spectroscopic datasets, such as nuclear magnetic resonance (NMR) spectra, to characterize biological systems depends on the elaboration of robust methods for cellular metabolites extraction. Previous studies have addressed many issues raised by these protocols, however with little pondering on ergonomic and practical aspects of the methods that impact their scalability, reproducibility and hence their suitability to high-throughput studies or their use by non-metabolomics experts. Here, we optimize a fast and ergonomic protocol for extraction of metabolites from adherent mammalian cells for NMR metabolomics studies. The proposed extraction protocol, including cell washing, metabolism quenching and actual extraction of intracellular metabolites, was first optimized on HeLa cells. Efficiency of the protocol, in its globality and for the different individual steps, was assessed by NMR quantification of 27 metabolites from cellular extracts. We show that a single PBS wash provides a seemly compromise between contamination from growth medium and leakage of intracellular metabolites. In HeLa cells, extraction using pure methanol, without cell scraping, recovered a higher amount of intracellular metabolites than the reference methanol/water/chloroform method with cell scraping, with yields varying across metabolite classes. Optimized and reference protocols were further tested on eight cell lines of miscellaneous nature, and inter-operator reproducibility was demonstrated. Our results stress the need for tailored extraction protocols and show that fast protocols minimizing time-consuming steps, without compromising extraction yields, are suitable for high-throughput metabolomics studies. Graphical abstract.

An improved extraction method enables the comprehensive analysis of lipids, proteins, metabolites and phytohormones from a single sample of leaf tissue under water-deficit stress.

Phytohormones play essential roles in the regulation of growth and development in plants. Plant hormone profiling is therefore essential to understand developmental processes and the adaptation of plants to biotic and/or abiotic stresses. Interestingly, commonly used hormone extraction and profiling methods do not adequately resolve other molecular entities, such as polar metabolites, lipids, starch and proteins, which would be required to comprehensively describe the continuing biological processes at a systematic level. In this article we introduce an updated version of a previously published liquid:liquid metabolite extraction protocol, which not only allows for the profiling of primary and secondary metabolites, lipids, starch and proteins, but also enables the quantitative analysis of the major plant hormone classes, including abscisic acid, auxins, cytokinins, jasmonates and salicylates, from a single sample aliquot. The optimization of the method, which uses the introduction of acidified water, enabling the complete purification of major plant hormones into the organic (methyl-tert-butyl-ether) phase, eliminated the need for solid-phase extraction for sample clean-up, and therefore reduces both sampling time and cost. As a proof-of-concept analysis, Arabidopsis thaliana plants were subjected to water-deficit stress, which were then profiled for hormonal, metabolic, lipidomic and proteomic changes. Surprisingly, we determined not only previously described molecular changes but also significant changes regarding the breakdown of specific galactolipids, followed by the substantial accumulation of unsaturated fatty-acid derivatives and diverse jasmonates in the course of adaptation to water-deficit stress.

Global alteration of T-lymphocyte metabolism by PD-L1 checkpoint involves a block of de novo nucleoside phosphate synthesis

Metabolic obstacles of the tumor microenvironment remain a challenge to T-cell-mediated cancer immunotherapies. To better understand the interplay of immune checkpoint signaling and immune metabolism, this study developed and used an optimized metabolite extraction protocol for non-adherent primary human T-cells, to broadly profile in vitro metabolic changes effected by PD-1 signaling by mass spectrometry-based metabolomics and isotopomer analysis. Inhibitory signaling reduced aerobic glycolysis and glutaminolysis. A general scarcity across the panel of metabolites measured supported widespread metabolic regulation by PD-1. Glucose carbon fate analysis supported tricarboxylic acid cycle reliance on pyruvate carboxylation, catabolic-state fluxes into acetyl-CoA and succinyl-CoA, and a block in de novo nucleoside phosphate synthesis that was accompanied by reduced mTORC1 signaling. Nonetheless, exogenous administration of nucleosides was not sufficient to ameliorate proliferation of T-cells in the context of multiple metabolic insufficiencies due to PD-L1 treatment. Carbon fate analysis did not support the use of primarily glucose-derived carbons to fuel fatty acid beta oxidation, in contrast to reports on T-memory cells. These findings add to our understanding of metabolic dysregulation by PD-1 signaling and inform the effort to rationally develop metabolic interventions coupled with immune-checkpoint blockade for increased treatment efficacy.

NMR Spectroscopy-Based Metabolic Profiling of Biospecimens.

Metabolomics refers to study of metabolites in biospecimens such as blood serum, tissues, and urine. Nuclear magnetic resonance (NMR) spectroscopy and ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS; mass spectrometry coupled with liquid chromatography) are most frequently employed to analyze complex biological/clinical samples. NMR is a relatively insensitive tool compared to UPLC-MS/MS but offers straightforward quantification and identification and easy sample processing. One-dimensional 1 H NMR spectroscopy is inherently quantitative and can be readily used for metabolite quantification without individual metabolite standards. Two-dimensional spectroscopy is most commonly used for identification of metabolites but can also be used quantitatively. Although NMR experiments are unbiased regarding the chemical nature of the analyte, it is crucial to adhere to the proper metabolite extraction protocol for optimum results. Selection and implementation of appropriate NMR pulse programs are also important. Finally, employment of the correct metabolite quantification strategy is crucial as well. In this unit, step-by-step guidance for running an NMR metabolomics experiment from typical biospecimens is presented. The unit describes an optimized metabolite extraction protocol, followed by implementation of NMR experiments and quantification strategies using the so-called "targeted profiling" technique. This approach relies on an underlying basis set of metabolite spectra acquired under similar conditions. Some strategies for statistical analysis of the data are also presented. Overall, this set of protocols should serve as a guide for anyone who wishes to enter the world of NMR-based metabolomics analysis. © 2019 by John Wiley & Sons, Inc. Basic Protocol 1: Metabolite extraction from different biospecimens Basic Protocol 2: Preparation of dried upper fraction for NMR analysis Alternate Protocol: Preparation of urine samples for NMR analysis Basic Protocol 3: NMR experiments Basic Protocol 4: Spectral processing and quantification of metabolites Basic Protocol 5: Statistical analysis of the data.

Optimization of Metabolite Extraction Protocols for Untargeted Metabolite Profiling of Mycoparasitic Scytalidium parasiticum using LC-TOF-MS

Basal stem rot disease of oil palm caused by Ganoderma boninense is one of the most devastating diseases in oil palm plantation resulting in low yield, loss of palm stands and shorter replanting cycle. To-date, there is no effective treatment for Ganoderma infected palms. Control measures, either chemical or cultural approaches, show varying degrees of effectiveness. The application of biological control agents which is environmental-friendly could be an attractive solution to overcome the problem. Earlier, we had isolated a mycoparasite, Scytalidium parasiticum, from the basidiomata of Ganoderma boninense. In vitro assay and nursery experiment showed that this fungus could suppress Ganoderma infection and reduce disease severity. However, metabolites which might contribute to the antagonistic or mycoparasitic effect remain unknown. In the current study, optimization of fungal sample processing, extraction, and analytical procedures were conducted to obtain metabolites from the maize substrate colonized by mycoparasitic ascomycetous Scytalidium parasiticum. This technique capable of producing sexual spores in sac-like organs. Untargeted metabolomics profiling was carried out by using Liquid Chromatography Time of Flight Mass Spectrometry (LC-ToF-MS). We found that S. parasiticum in both liquid- and solid-state cultivation gave higher metabolite when extracted with 60% methanol with 1% formic acid in combination with homogenisation methods such as ultrasonication and grinding. The findings from this study are useful for optimisation of metabolite extraction from other fungi-Ganoderma-plant interactions.

Antioxidant response of cucumber (Cucumis sativus) exposed to nano copper pesticide: Quantitative determination via LC-MS/MS

Targeted metabolomics aims to provide a new approach to investigate metabolites and gather both qualitative and quantitative information. We describe a protocol for extraction and analysis of plant metabolites, specifically 13 secondary metabolites (antioxidants) using liquid chromatography coupled to triple quadrupole mass spectrometry (LC-MS/MS), with high linearity (R2 > 0.99) and reproducibility (0.23–6.23 R%) with low limits of detection (>0.001 ng/mL) and quantification (>0.2 ng/mL). The protocol was applied to study the antioxidant response of cucumber plants exposed to nanocopper pesticide. Dose-dependent changes in antioxidant concentrations were found, and 10 antioxidants were significantly consumed to scavenge reactive oxygen species, protecting plants from damage. Levels of three antioxidants were up-regulated, as a response to the depletion of the other antioxidants, signaling activation of the defense system. We demonstrated that the reported LC-MS/MS method provides a quantitative analysis of antioxidants in plant tissues, for example to investigate interactions between plants and nanomaterials.

Engineered Production of Short-Chain Acyl-Coenzyme A Esters in Saccharomyces cerevisiae.

Short-chain acyl-coenzyme A esters serve as intermediate compounds in fatty acid biosynthesis, and the production of polyketides, biopolymers and other value-added chemicals. S.cerevisiae is a model organism that has been utilized for the biosynthesis of such biologically and economically valuable compounds. However, its limited repertoire of short-chain acyl-CoAs effectively prevents its application as a production host for a plethora of natural products. Therefore, we introduced biosynthetic metabolic pathways to five different acyl-CoA esters into S.cerevisiae. Our engineered strains provide the following acyl-CoAs: propionyl-CoA, methylmalonyl-CoA, n-butyryl-CoA, isovaleryl-CoA and n-hexanoyl-CoA. We established a yeast-specific metabolite extraction protocol to determine the intracellular acyl-CoA concentrations in the engineered strains. Propionyl-CoA was produced at 4-9 μM; methylmalonyl-CoA at 0.5 μM; and isovaleryl-CoA, n-butyryl-CoA, and n-hexanoyl-CoA at 6 μM each. The acyl-CoAs produced in this study are common building blocks of secondary metabolites and will enable the engineered production of a variety of natural products in S.cerevisiae. By providing this toolbox of acyl-CoA producing strains, we have laid the foundation to explore S.cerevisiae as a heterologous production host for novel secondary metabolites.

High-throughput extraction and quantification method for targeted metabolomics in murine tissues

IntroductionGlobal metabolomics analyses using body fluids provide valuable results for the understanding and prediction of diseases. However, the mechanism of a disease is often tissue-based and it is advantageous to analyze metabolomic changes directly in the tissue. Metabolomics from tissue samples faces many challenges like tissue collection, homogenization, and metabolite extraction.ObjectivesWe aimed to establish a metabolite extraction protocol optimized for tissue metabolite quantification by the targeted metabolomics AbsoluteIDQ™ p180 Kit (Biocrates). The extraction method should be non-selective, applicable to different kinds and amounts of tissues, monophasic, reproducible, and amenable to high throughput.MethodsWe quantified metabolites in samples of eleven murine tissues after extraction with three solvents (methanol, phosphate buffer, ethanol/phosphate buffer mixture) in two tissue to solvent ratios and analyzed the extraction yield, ionization efficiency, and reproducibility.ResultsWe found methanol and ethanol/phosphate buffer to be superior to phosphate buffer in regard to extraction yield, reproducibility, and ionization efficiency for all metabolites measured. Phosphate buffer, however, outperformed both organic solvents for amino acids and biogenic amines but yielded unsatisfactory results for lipids. The observed matrix effects of tissue extracts were smaller or in a similar range compared to those of human plasma.ConclusionWe provide for each murine tissue type an optimized high-throughput metabolite extraction protocol, which yields the best results for extraction, reproducibility, and quantification of metabolites in the p180 kit. Although the performance of the extraction protocol was monitored by the p180 kit, the protocol can be applicable to other targeted metabolomics assays.

The combination of four analytical methods to explore skeletal muscle metabolomics: Better coverage of metabolic pathways or a marketing argument?

ObjectivesMetabolomics is an emerging science based on diverse high throughput methods that are rapidly evolving to improve metabolic coverage of biological fluids and tissues. Technical progress has led researchers to combine several analytical methods without reporting the impact on metabolic coverage of such a strategy. The objective of our study was to develop and validate several analytical techniques (mass spectrometry coupled to gas or liquid chromatography and nuclear magnetic resonance) for the metabolomic analysis of small muscle samples and evaluate the impact of combining methods for more exhaustive metabolite covering. Design and methodsWe evaluated the muscle metabolome from the same pool of mouse muscle samples after 2 metabolite extraction protocols. Four analytical methods were used: targeted flow injection analysis coupled with mass spectrometry (FIA-MS/MS), gas chromatography coupled with mass spectrometry (GC–MS), liquid chromatography coupled with high-resolution mass spectrometry (LC–HRMS), and nuclear magnetic resonance (NMR) analysis. We evaluated the global variability of each compound i.e., analytical (from quality controls) and extraction variability (from muscle extracts). We determined the best extraction method and we reported the common and distinct metabolites identified based on the number and identity of the compounds detected with low analytical variability (variation coefficient<30%) for each method. Finally, we assessed the coverage of muscle metabolic pathways obtained. ResultsMethanol/chloroform/water and water/methanol were the best extraction solvent for muscle metabolome analysis by NMR and MS, respectively. We identified 38 metabolites by nuclear magnetic resonance, 37 by FIA-MS/MS, 18 by GC–MS, and 80 by LC–HRMS. The combination led us to identify a total of 132 metabolites with low variability partitioned into 58 metabolic pathways, such as amino acid, nitrogen, purine, and pyrimidine metabolism, and the citric acid cycle. This combination also showed that the contribution of GC–MS was low when used in combination with other mass spectrometry methods and nuclear magnetic resonance to explore muscle samples. ConclusionThis study reports the validation of several analytical methods, based on nuclear magnetic resonance and several mass spectrometry methods, to explore the muscle metabolome from a small amount of tissue, comparable to that obtained during a clinical trial. The combination of several techniques may be relevant for the exploration of muscle metabolism, with acceptable analytical variability and overlap between methods However, the difficult and time-consuming data pre-processing, processing, and statistical analysis steps do not justify systematically combining analytical methods.

GC-MS based metabolomics of colon cancer cells using different extraction solvents

The increasing incidence of colorectal cancer enforces the development of novel methodologies and protocols to deepen in the molecular mechanisms that govern disease pathophysiological events. The aim of this work is to deepen in the optimum metabolite extraction protocol from adherent mammalian cells of colon cancer for high throughput metabolomics using gas chromatography coupled to mass spectrometry (GC-MS). GC-MS results showed that metabolic information obtained from colon cancer cells was highly dependent on metabolite extraction selection, which at the same time is extremely influenced by the analytical platform. A further purpose of this investigation is to uncover an unexplored portion of HT-29 colon cancer cells metabolome, complementary to other already explored by CE-MS and LC-MS methods. At this respect, a total of 150 metabolites were identified in HT-29 colon cancer cells by GC-MS. The extraction protocol with acetonitrile-isopropanol-water was the most appropriate for fatty acids and related pathways analysis. Most of the metabolites involved in pathways of amino acids, glutathione, amino sugars and other polar metabolites were better extracted with acidified water, although water extraction showed the best overall reproducibility. Although pathways involving nitrogenous bases could be investigated using organic or aqueous extracts, a higher number of metabolites involved in these pathways were identified in the aqueous extracts. In addition, metabolite extraction protocol was observed to be crucial for the determination of potentially interesting clusters of metabolites.

Optimizing 2D gas chromatography mass spectrometry for robust tissue, serum and urine metabolite profiling

Two-dimensional gas chromatography mass spectrometry (GCxGC-MS) is utilized to an increasing extent in biomedical metabolomics. Here, we established and adapted metabolite extraction and derivatization protocols for cell/tissue biopsy, serum and urine samples according to their individual properties. GCxGC-MS analysis revealed detection of ~600 molecular features from which 165 were characterized representing different classes such as amino acids, fatty acids, lipids, carbohydrates, nucleotides and small polar components of glycolysis and the Krebs cycle using electron impact (EI) spectrum matching and validation using external standard compounds. Advantages of two-dimensional gas chromatography based resolution were demonstrated by optimizing gradient length and separation through modulation between the first and second column, leading to a marked increase in metabolite identification due to improved separation as exemplified for lactate versus pyruvate, talopyranose versus methyl palmitate and inosine versus docosahexaenoic acid. Our results demonstrate that GCxGC-MS represents a robust metabolomics platform for discovery and targeted studies that can be used with samples derived from the clinic.