Design of experiments: an efficient strategy to identify factors influencing extraction and derivatization of Arabidopsis thaliana samples in metabolomic studies with gas chromatography/mass spectrometry

Mass spectrometry-based forest tree metabolomics

Research in forest tree species has advanced slowly when compared with other agricultural crops and model organisms, mainly due to the long-life cycles, large genome sizes, and lack of genomic tools. Additionally, trees are complex matrices, and the presence of interferents (e.g., oleoresins and cellulose) challenges the analysis of tree tissues with mass spectrometry (MS)-based analytical platforms. In this review, advances in MS-based forest tree metabolomics are discussed. Given their economic and ecological significance, particular focus is given to Pinus, Quercus, and Eucalyptus forest tree species to better understand their metabolite responses to abiotic and biotic stresses in the current climate change scenario. Furthermore, MS-based metabolomics technologies produce large and complex datasets that require expertize to adequately manage, process, analyze, and store the data in dedicated repositories. To ensure that the full potential of forest tree metabolomics data are translated into new knowledge, these data should comply with the FAIR principles (i.e., Findable, Accessible, Interoperable, and Re-usable). It is essential that adequate standards are implemented to annotate metadata from forest tree metabolomics studies as is already required by many science and governmental agencies and some major scientific publishers. © 2019 John Wiley & Sons Ltd. Mass Spec Rev 40:126-157, 2021.

Sucrose synthase determines carbon allocation in developing wood and alters carbon flow at the whole tree level in aspen

Despite the ecological and industrial importance of biomass accumulation in wood, the control of carbon (C) allocation to this tissue and to other tree tissues remain poorly understood. We studied sucrose synthase (SUS) to clarify its role in biomass formation and C metabolism at the whole tree level in hybrid aspen (Populus tremula × tremuloides). To this end, we analysed source leaves, phloem, developing wood, and roots of SUSRNAi trees using a combination of metabolite profiling, ¹³ CO₂ pulse labelling experiments, and long-term field experiments. The glasshouse grown SUSRNAi trees exhibited a mild stem phenotype together with a reduction in wood total C. The ¹³ CO₂ pulse labelling experiments showed an alteration in the C flow in all the analysed tissues, indicating that SUS affects C metabolism at the whole tree level. This was confirmed when the SUSRNAi trees were grown in the field over a 5-yr period; their stem height, diameter and biomass were substantially reduced. These results establish that SUS influences C allocation to developing wood, and that it affects C metabolism at the whole tree level.

Metallothionein 1 Overexpression Does Not Protect Against Mitochondrial Disease Pathology in Ndufs4 Knockout Mice

Mitochondrial diseases (MD), such as Leigh syndrome (LS), present with severe neurological and muscular phenotypes in patients, but have no known cure and limited treatment options. Based on their neuroprotective effects against other neurodegenerative diseases in vivo and their positive impact as an antioxidant against complex I deficiency in vitro, we investigated the potential protective effect of metallothioneins (MTs) in an Ndufs4 knockout mouse model (with a very similar phenotype to LS) crossed with an Mt1 overexpressing mouse model (TgMt1). Despite subtle reductions in the expression of neuroinflammatory markers GFAP and IBA1 in the vestibular nucleus and hippocampus, we found no improvement in survival, growth, locomotor activity, balance, or motor coordination in the Mt1 overexpressing Ndufs4-/- mice. Furthermore, at a cellular level, no differences were detected in the metabolomics profile or gene expression of selected one-carbon metabolism and oxidative stress genes, performed in the brain and quadriceps, nor in the ROS levels of macrophages derived from these mice. Considering these outcomes, we conclude that MT1, in general, does not protect against the impaired motor activity or improve survival in these complex I-deficient mice. The unexpected absence of increased oxidative stress and metabolic redox imbalance in this MD model may explain these observations. However, tissue-specific observations such as the mildly reduced inflammation in the hippocampus and vestibular nucleus, as well as differential MT1 expression in these tissues, may yet reveal a tissue- or cell-specific role for MTs in these mice.

A comprehensive comparison of four methods for extracting lipids from Arabidopsis tissues

BACKGROUND

The plant lipidome is highly complex, and the composition of lipids in different tissues as well as their specific functions in plant development, growth and stress responses have yet to be fully elucidated. To do this, efficient lipid extraction protocols which deliver target compounds in solution at concentrations adequate for subsequent detection, quantitation and analysis through spectroscopic methods are required. To date, numerous methods are used to extract lipids from plant tissues. However, a comprehensive analysis of the efficiency and reproducibility of these methods to extract multiple lipid classes from diverse tissues of a plant has not been undertaken.

RESULTS

In this study, we report the comparison of four different lipid extraction procedures in order to determine the most effective lipid extraction protocol to extract lipids from different tissues of the model plant Arabidopsis thaliana.

CONCLUSION

While particular methods were best suited to extract different lipid classes from diverse Arabidopsis tissues, overall a single-step extraction method with a 24 h extraction period, which uses a mixture of chloroform, isopropanol, methanol and water, was the most efficient, reproducible and the least labor-intensive to extract a broad range of lipids for untargeted lipidomic analysis of Arabidopsis tissues. This method extracted a broad range of lipids from leaves, stems, siliques, roots, seeds, seedlings and flowers of Arabidopsis. In addition, appropriate methods for targeted lipid analysis of specific lipids from particular Arabidopsis tissues were also identified.

A metabolite roadmap of the wood-forming tissue in Populus tremula

Wood, or secondary xylem, is the product of xylogenesis, a developmental process that begins with the proliferation of cambial derivatives and ends with mature xylem fibers and vessels with lignified secondary cell walls. Fully mature xylem has undergone a series of cellular processes, including cell division, cell expansion, secondary wall formation, lignification and programmed cell death. A complex network of interactions between transcriptional regulators and signal transduction pathways controls wood formation. However, the role of metabolites during this developmental process has not been comprehensively characterized. To evaluate the role of metabolites during wood formation, we performed a high spatial resolution metabolomics study of the wood-forming zone of Populus tremula, including laser dissected aspen ray and fiber cells. We show that metabolites show specific patterns within the wood-forming zone, following the differentiation process from cell division to cell death. The data from profiled laser dissected aspen ray and fiber cells suggests that these two cell types host distinctly different metabolic processes. Furthermore, by integrating previously published transcriptomic and proteomic profiles generated from the same trees, we provide an integrative picture of molecular processes, for example, deamination of phenylalanine during lignification is of critical importance for nitrogen metabolism during wood formation.

Investigation of Organic Acids in Saffron Stigmas (Crocus sativus L.) Extract by Derivatization Method and Determination by GC/MS

The beneficial health properties of organic acids make them target compounds in multiple studies. This is the reason why developing a simple and sensitive determination and investigation method of organic acids is a priority. In this study, an effective method has been established for the determination of organic (lactic, glycolic, and malic) acids in saffron stigmas. N-(tert-butyldimethylsilyl)-N-methyltrifluoroacetamide (MTBSTFA) was used as a derivatization reagent in gas chromatography combined with mass spectrometric detection (GC/MS). The saffron stigmas extract was evaporated to dryness with a stream of nitrogen gas. The derivatization procedure: 0.1 g of dried extract was diluted into 0.1 mL of tetrahydrofuran, then 0.1 mL MTBSTFA was orderly and successively added into a vial. Two different techniques were used to obtain the highest amount of organic acid derivatives from saffron stigmas. To the best of our knowledge, this is the first report of the quantitative and qualitative GC/MS detection of organic acids in saffron stigmas using MTBSTFA reagent, also comparing different derivatization conditions, such as time, temperature and the effect of reagent amount on derivatization process. The identification of these derivatives was performed via GC-electron impact ionization mass spectrometry in positive-ion detection mode. Under optimal conditions, excellent linearity for all organic acids was obtained with determination coefficients of R² > 0.9955. The detection limits (LODs) and quantitation limits (LOQs) ranged from 0.317 to 0.410 µg/mL and 0.085 to 1.53 µg/mL, respectively. The results showed that the highest yield of organic acids was conducted by using 0.1 mL of MTBSTFA and derivatization method with a conventional heating process at 130 °C for 90 min. This method has been successfully applied to the quantitative analysis of organic acids in saffron stigmas.

Novel mitochondrial and cytosolic purification pipeline for compartment-specific metabolomics in mammalian disease model tissues

INTRODUCTION

Mitochondria represent an important milieu for studying the pathogenesis of several major diseases. The need for organelle-level metabolic resolution exists, as mitochondrial/cytosolic metabolites are often diluted beyond detection limits in complex samples. Compartment-specific studies are still hindered by the lack of efficient, cost-effective fractioning methods-applicable to laboratories of all financial/analytical standing.

OBJECTIVES

We established a novel mitochondrial/cytosolic purification pipeline for complimentary GC-TOF-MS and ¹H-NMR metabolomics using robust, commercially available fractionation strategies.

METHODS

Magnetic based mitochondria isolation kits (MACS) were adapted for this purpose, accompanied by cytosolic filtering. Yield was assessed through the percentage recovery of citrate synthase (CS; a mitochondrial marker), purity by immunoblotting against compartment-specific proteins and integrity interrogated through the respiratory coupling ratio (RCR). The effects of the kit-based buffers on MS/NMR analyses of pure metabolite standards were evaluated. Finally, biological applicability to mammalian disease models was shown using Ndufs4 mouse brain tissue.

RESULTS

With minor modifications, MACS produced around 60% more mitochondria compared to a differential centrifugation method. Less than 15% of lysosomal LAMP-2 protein was found in the MACS isolates, confirming relative purity-while RCR's above 6 indicate sufficient mitochondrial integrity. The filtering approach effectively depleted mitochondria from the cytosolic fraction, as indicated by negligible Hsp60 and CS levels. Our GC-MS pilot yielded 60-70 features per fraction, while NMR analyses could quantify 6-10 of the most abundant compounds in each fraction.

CONCLUSION

This study provides a simple and flexible solution for mitochondrial and cytosolic metabolomics in animal model tissues, towards large-scale application of such methodologies in disease research.

Ecometabolomics for a Better Understanding of Plant Responses and Acclimation to Abiotic Factors Linked to Global Change

The number of ecometabolomic studies, which use metabolomic analyses to disentangle organisms' metabolic responses and acclimation to a changing environment, has grown exponentially in recent years. Here, we review the results and conclusions of ecometabolomic studies on the impacts of four main drivers of global change (increasing frequencies of drought episodes, heat stress, increasing atmospheric carbon dioxide (CO2) concentrations and increasing nitrogen (N) loads) on plant metabolism. Ecometabolomic studies of drought effects confirmed findings of previous target studies, in which most changes in metabolism are characterized by increased concentrations of soluble sugars and carbohydrate derivatives and frequently also by elevated concentrations of free amino acids. Secondary metabolites, especially flavonoids and terpenes, also commonly exhibited increased concentrations when drought intensified. Under heat and increasing N loads, soluble amino acids derived from glutamate and glutamine were the most responsive metabolites. Foliar metabolic responses to elevated atmospheric CO2 concentrations were dominated by greater production of monosaccharides and associated synthesis of secondary metabolites, such as terpenes, rather than secondary metabolites synthesized along longer sugar pathways involving N-rich precursor molecules, such as those formed from cyclic amino acids and along the shikimate pathway. We suggest that breeding for crop genotypes tolerant to drought and heat stress should be based on their capacity to increase the concentrations of C-rich compounds more than the concentrations of smaller N-rich molecules, such as amino acids. This could facilitate rapid and efficient stress response by reducing protein catabolism without compromising enzymatic capacity or increasing the requirement for re-transcription and de novo biosynthesis of proteins.

Lipid accumulation controls the balance between surface connection and scission of caveolae

Caveolae are bulb-shaped invaginations of the plasma membrane (PM) that undergo scission and fusion at the cell surface and are enriched in specific lipids. However, the influence of lipid composition on caveolae surface stability is not well described or understood. Accordingly, we inserted specific lipids into the cell PM via membrane fusion and studied their acute effects on caveolae dynamics. We demonstrate that sphingomyelin stabilizes caveolae to the cell surface, whereas cholesterol and glycosphingolipids drive caveolae scission from the PM. Although all three lipids accumulated specifically in caveolae, cholesterol and sphingomyelin were actively sequestered, whereas glycosphingolipids diffused freely. The ATPase EHD2 restricts lipid diffusion and counteracts lipid-induced scission. We propose that specific lipid accumulation in caveolae generates an intrinsically unstable domain prone to scission if not restrained by EHD2 at the caveolae neck. This work provides a mechanistic link between caveolae and their ability to sense the PM lipid composition.

Selective and Accurate Quantification of N-Acetylglucosamine in Biotechnological Cell Samples via GC-MS/MS and GC-TOFMS

N-Acetylglucosamine is a key component of bacterial and fungal cell walls and of the extracellular matrix of animal cells. It plays a variety of roles at the cell surface structure and is under discussion to be involved in signaling pathways. The presence of a number of N-acetylhexosamine stereoisomers in samples of biological or biotechnological origin demands for dedicated high efficiency separation methods, due to identical exact mass and similar fragmentation patterns of the stereoisomers. Gas chromatography offers high sample capacity, separation efficiency, and precision under repeatability conditions of measurement, which is a necessity for the analysis of low abundant stereoisomers in biological samples. Automated online derivatization facilitates to overcome the main obstacle for the use of gas chromatography in metabolomics, namely, the derivatization of polar metabolites prior to analysis. Using alkoximation and subsequent trimethylsilylation, carbohydrates and their derivatives are known to show several derivatives, since derivatization is incomplete as well as highly matrix dependent inherent to the high number of functional groups present in carbohydrates. A method based on efficient separation of ethoximated and trimethylsilylated N-acetylglucosamines was developed. Accurate absolute quantification is enabled using biologically derived ¹³C labeled internal standards eliminating systematic errors related to sample pretreatment and analysis. Due to the lack of certified reference materials, a methodological comparison between tandem and time-of-flight mass spectrometric instrumentation was performed for mass spectrometric assessment of trueness. Both methods showed limits of detection in the lower femtomol range. The methods were applied to biological samples of Penicillium chrysogenum cultivations with different matrices revealing excellent agreement of both mass spectrometric techniques.

Integrated Univariate, Multivariate, and Correlation-Based Network Analyses Reveal Metabolite-Specific Effects on Bacterial Growth and Biofilm Formation in Necrotizing Soft Tissue Infections

Necrotizing soft-tissue infections (NSTIs) have multiple causes, risk factors, anatomical locations, and pathogenic mechanisms. In patients with NSTI, circulating metabolites may serve as a substrate having impact on bacterial adaptation at the site of infection. Metabolic signatures associated with NSTI may reveal the potential to be useful as diagnostic and prognostic markers and novel targets for therapy. This study used untargeted metabolomics analyses of plasma from NSTI patients (n = 34) and healthy (noninfected) controls (n = 24) to identify the metabolic signatures and connectivity patterns among metabolites associated with NSTI. Metabolite-metabolite association networks were employed to compare the metabolic profiles of NSTI patients and noninfected surgical controls. Out of 97 metabolites detected, the abundance of 33 was significantly altered in NSTI patients. Analysis of metabolite-metabolite association networks showed a more densely connected network: specifically, 20 metabolites differentially connected between NSTI and controls. A selected set of significantly altered metabolites was tested in vitro to investigate potential influence on NSTI group A streptococcal strain growth and biofilm formation. Using chemically defined media supplemented with the selected metabolites, ornithine, ribose, urea, and glucuronic acid, revealed metabolite-specific effects on both bacterial growth and biofilm formation. This study identifies for the first time an NSTI-specific metabolic signature with implications for optimized diagnostics and therapies.

Experimental Design and Sample Preparation in Forest Tree Metabolomics

Appropriate experimental design and sample preparation are key steps in metabolomics experiments, highly influencing the biological interpretation of the results. The sample preparation workflow for plant metabolomics studies includes several steps before metabolite extraction and analysis. These include the optimization of laboratory procedures, which should be optimized for different plants and tissues. This is particularly the case for trees, whose tissues are complex matrices to work with due to the presence of several interferents, such as oleoresins, cellulose. A good experimental design, tree tissue harvest conditions, and sample preparation are crucial to ensure consistency and reproducibility of the metadata among datasets. In this review, we discuss the main challenges when setting up a forest tree metabolomics experiment for mass spectrometry (MS)-based analysis covering all technical aspects from the biological question formulation and experimental design to sample processing and metabolite extraction and data acquisition. We also highlight the importance of forest tree metadata standardization in metabolomics studies.

Effect of ILK on small-molecule metabolism of human periodontal ligament fibroblasts with mechanical stretching

BACKGROUND

Mechanical stimuli can cause periodontal tissue reconstruction. Studies have found that changes in metabolites can be the terminal effect of integrin-mediated mechanical signaling. As a key kinase in integrin regulation, integrin-linked kinase (ILK) mediates mechanical signal transduction, which may contribute to metabolite changes. Defining the components of small-molecule metabolites can optimize mechanical stimuli and periodontal tissue reconstruction. Our purpose is to detect the effect of ILK-mediated mechanical signaling on intracellular small-molecule metabolites (amino acids and organic acids) in human periodontal ligament fibroblasts (HPDLFs).

METHODS

Primary HPDLFs were isolated by enzyme digestion method. Tensile stresses were applied on HPDLFs in vitro using a Flexcell system. ILK gene in HPDLFs was knocked down by RNA interference (RNAi). Twenty common amino acids and seven organic acids in HPDLFs were analyzed by gas chromatography/mass spectrometry technique.

RESULTS

Five amino acids (ie, alanine, glutamine, glutamate, glycine, and threonine) and three organic acids (ie, pyruvate, lactate, and citric acid) were found to be changed remarkably after mechanical stretching. In addition, baseline levels of four amino acids (ie, glutamate, glutamine, threonine, and glycine) and two organic acids (ie, lactate and citric acid) were significantly different in ILK knockdown compared with wild-type HPDLFs.

CONCLUSION

This study suggests that five amino acids (ie, alanine, glutamine, glutamate, glycine, and threonine) and three organic acids (ie, pyruvate, lactate, and citric acid) may act as cellular mediators for mechanical signals in HPDLFs. Among them, four amino acids (ie, glutamate, glutamine, threonine, and glycine) and two organic acids (ie, lactate and citric acid) may be closely linked to ILK.

Leaf metabolic signatures induced by real and simulated herbivory in black mustard (Brassica nigra)

INTRODUCTION

The oxylipin methyl jasmonate (MeJA) is a plant hormone active in response signalling and defence against herbivores. Although MeJA is applied experimentally to mimic herbivory and induce plant defences, its downstream effects on the plant metabolome are largely uncharacterized, especially in the context of primary growth and tissue-specificity of the response.

OBJECTIVES

We investigated the effects of MeJA-simulated and real caterpillar herbivory on the foliar metabolome of the wild plant Brassica nigra and monitored the herbivore-induced responses in relation to leaf ontogeny.

METHODS

As single or multiple herbivory treatments, MeJA- and mock-sprayed plants were consecutively exposed to caterpillars or left untreated. Gas chromatography (GC) and liquid chromatography (LC) time-of-flight mass-spectrometry (TOF-MS) were combined to analyse foliar compounds, including central primary and specialized defensive plant metabolites.

RESULTS

Plant responses were stronger in young leaves, which simultaneously induced higher chlorophyll levels. Both MeJA and caterpillar herbivory induced similar, but not identical, accumulation of tricarboxylic acids (TCAs), glucosinolates (GSLs) and phenylpropanoids (PPs), but only caterpillar feeding led to depletion of amino acids. MeJA followed by caterpillars caused higher induction of defence compounds, including a three-fold increase in the major defence compound allyl-GSL (sinigrin). When feeding on MeJA-treated plants, caterpillars gained less weight indicative of the reduced host-plant quality and enhanced resistance.

CONCLUSIONS

The metabolomics approach showed that plant responses induced by herbivory extend beyond the regulation of defence metabolism and are tightly modulated throughout leaf development. This leads to a new understanding of the plant metabolic potential that can be exploited for future plant protection strategies.

Oncogenic KRAS Induces NIX-Mediated Mitophagy to Promote Pancreatic Cancer

Activating KRAS mutations are found in nearly all cases of pancreatic ductal adenocarcinoma (PDAC), yet effective clinical targeting of oncogenic KRAS remains elusive. Understanding of KRAS-dependent PDAC-promoting pathways could lead to the identification of vulnerabilities and the development of new treatments. We show that oncogenic KRAS induces BNIP3L/NIX expression and a selective mitophagy program that restricts glucose flux to the mitochondria and enhances redox capacity. Loss of Nix restores functional mitochondria to cells, increasing demands for NADPH reducing power and decreasing proliferation in glucose-limited conditions. Nix deletion markedly delays progression of pancreatic cancer and improves survival in a murine (KPC) model of PDAC. Although conditional Nix ablation in vivo initially results in the accumulation of mitochondria, mitochondrial content eventually normalizes via increased mitochondrial clearance programs, and pancreatic intraepithelial neoplasia (PanIN) lesions progress to PDAC. We identify the KRAS-NIX mitophagy program as a novel driver of glycolysis, redox robustness, and disease progression in PDAC. SIGNIFICANCE: NIX-mediated mitophagy is a new oncogenic KRAS effector pathway that suppresses functional mitochondrial content to stimulate cell proliferation and augment redox homeostasis. This pathway promotes the progression of PanIN to PDAC and represents a new dependency in pancreatic cancer.This article is highlighted in the In This Issue feature, p. 1143.

Nontargeted Detection Methods for Food Safety and Integrity

Nontargeted workflows for chemical hazard analyses are highly desirable in the food safety and integrity fields to ensure human health. Two different analytical strategies, nontargeted metabolomics and chemical database filtering, can be used to screen unknown contaminants in food matrices. Sufficient mass and chromatographic resolutions are necessary for the detection of compounds and subsequent componentization and interpretation of candidate ions. Analytical chemistry–based technologies, including gas chromatography–mass spectrometry (GC-MS), liquid chromatography–mass spectrometry (LC-MS), nuclear magnetic resonance (NMR), and capillary electrophoresis–mass spectrometry (CE-MS), combined with chemometrics analysis are being used to generate molecular formulas of compounds of interest. The construction of a chemical database plays a crucial role in nontargeted detection. This review provides an overview of the current sample preparation, analytical chemistry–based techniques, and data analysis as well as the limitations and challenges of nontargeted detection methods for analyzing complex food matrices. Improvements in sample preparation and analytical platforms may enhance the relevance of food authenticity, quality, and safety.

Metabolomics Provides Valuable Insight for the Study of Durum Wheat: A Review

Metabolomics is increasingly being applied in various fields offering a highly informative tool for high-throughput diagnostics. However, in plant sciences, metabolomics is underused, even though plant studies are relatively easy and cheap when compared to those on humans and animals. Despite their importance for human nutrition, cereals, and especially wheat, remain understudied from a metabolomics point of view. The metabolomics of durum wheat has been essentially neglected, although its genetic structure allows the inference of common mechanisms that can be extended to other wheat and cereal species. This review covers the present achievements in durum wheat metabolomics highlighting the connections with the metabolomics of other cereal species (especially bread wheat). We discuss the metabolomics data from various studies and their relationships to other "-omics" sciences, in terms of wheat genetics, abiotic and biotic stresses, beneficial microbes, and the characterization and use of durum wheat as feed, food, and food ingredient.

Atmo-ecometabolomics: a novel atmospheric particle chemical characterization methodology for ecological research

Aerosol particles play important roles in processes controlling the composition of the atmosphere and function of ecosystems. A better understanding of the composition of aerosol particles is beginning to be recognized as critical for ecological research to further comprehend the link between aerosols and ecosystems. While chemical characterization of aerosols has been practiced in the atmospheric science community, detailed methodology tailored to the needs of ecological research does not exist yet. In this study, we describe an efficient methodology (atmo-ecometabolomics), in step-by-step details, from the sampling to the data analyses, to characterize the chemical composition of aerosol particles, namely atmo-metabolome. This method employs mass spectrometry platforms such as liquid and gas chromatography mass spectrometries (MS) and Fourier transform ion cyclotron resonance MS (FT-ICR-MS). For methodology evaluation, we analyzed aerosol particles collected during two different seasons (spring and summer) in a low-biological-activity ecosystem. Additionally, to further validate our methodology, we analyzed aerosol particles collected in a more biologically active ecosystem during the pollination peaks of three different representative tree species. Our statistical results showed that our sampling and extraction methods are suitable for characterizing the atmo-ecometabolomes in these two distinct ecosystems with any of the analytical platforms. Datasets obtained from each mass spectrometry instrument showed overall significant differences of the atmo-ecometabolomes between spring and summer as well as between the three pollination peak periods. Furthermore, we have identified several metabolites that can be attributed to pollen and other plant-related aerosol particles. We additionally provide a basic guide of the potential use ecometabolomic techniques on different mass spectrometry platforms to accurately analyze the atmo-ecometabolomes for ecological studies. Our method represents an advanced novel approach for future studies in the impact of aerosol particle chemical compositions on ecosystem structure and function and biogeochemistry.

The Eucalyptus Cuticular Waxes Contribute in Preformed Defense Against Austropuccinia psidii

Austropuccinia psidii, the causal agent of myrtle rust, is a biotrophic pathogen whose growth and development depends on the host tissues. The uredospores of A. psidii infect Eucalyptus by engaging in close contact with the host surface and interacting with the leaf cuticle that provides important chemical and physical signals to trigger the infection process. In this study, the cuticular waxes of Eucalyptus spp. were analyzed to determine their composition or structure and correlation with susceptibility/resistance to A. psidii. Twenty-one Eucalyptus spp. in the field were classified as resistant or susceptible. The resistance/susceptibility level of six Eucalyptus spp. were validated in controlled conditions using qPCR, revealing that the pathogen can germinate on the eucalyptus surface of some species without multiplying in the host. CG-TOF-MS analysis detected 26 compounds in the Eucalyptus spp. cuticle and led to the discovery of the role of hexadecanoic acid in the susceptibility of Eucalyptus grandis and Eucalyptus phaeotricha to A. psidii. We characterized the epicuticular wax morphology of the six previously selected Eucalyptus spp. using scanning electron microscopy and observed different behavior in A. psidii germination during host infection. It was found a correlation of epicuticular morphology on the resistance to A. psidii. However, in this study, we provide the first report of considerable interspecific variation in Eucalyptus spp. on the susceptibility to A. psidii and its correlation with cuticular waxes chemical compounds that seem to play a synergistic role as a preformed defense mechanism.

Network Analyses and Data Integration of Proteomics and Metabolomics From Leaves of Two Contrasting Varieties of Sugarcane in Response to Drought

Uncovering the molecular mechanisms involved in the responses of crops to drought is crucial to understand and enhance drought tolerance mechanisms. Sugarcane (Saccharum spp.) is an important commercial crop cultivated mainly in tropical and subtropical areas for sucrose and ethanol production. Usually, drought tolerance has been investigated by single omics analysis (e.g. global transcripts identification). Here we combine label-free quantitative proteomics and metabolomics data (GC-TOF-MS), using a network-based approach, to understand how two contrasting commercial varieties of sugarcane, CTC15 (tolerant) and SP90-3414 (susceptible), adjust their leaf metabolism in response to drought. To this aim, we propose the utilization of regularized canonical correlation analysis (rCCA), which is a modification of classical CCA, and explores the linear relationships between two datasets of quantitative variables from the same experimental units, with a threshold set to 0.99. Light curves revealed that after 4 days of drought, the susceptible variety had its photosynthetic capacity already significantly reduced, while the tolerant variety did not show major reduction. Upon 12 days of drought, photosynthesis in the susceptible plants was completely reduced, while the tolerant variety was at a third of its rate under control conditions. Network analysis of proteins and metabolites revealed that different biological process had a stronger impact in each variety (e.g. translation in CTC15, generation of precursor metabolites, response to stress and energy in SP90-3414). Our results provide a reference data set and demonstrate that rCCA can be a powerful tool to infer experimentally metabolite-protein or protein-metabolite associations to understand plant biology.

Two-step derivatization for determination of sugar phosphates in plants by combined reversed phase chromatography/tandem mass spectrometry

BACKGROUND

Sugar phosphates are important intermediates of central carbon metabolism in biological systems, with roles in glycolysis, the pentose-phosphate pathway, tricarboxylic acid (TCA) cycle, and many other biosynthesis pathways. Understanding central carbon metabolism requires a simple, robust and comprehensive analytical method. However, sugar phosphates are notoriously difficult to analyze by traditional reversed phase liquid chromatography.

RESULTS

Here, we show a two-step derivatization of sugar phosphates by methoxylamine and propionic acid anhydride after chloroform/methanol (3:7) extraction from Populus leaf and developing wood that improves separation, identification and quantification of sugar phosphates by ultra high performance liquid chromatography-electrospray ionization-mass spectrometry (UHPLC-ESI-MS). Standard curves of authentic sugar phosphates were generated for concentrations from pg to ng/μl with a correlation coefficient R ² > 0.99. The method showed high sensitivity and repeatability with relative standard deviation (RSD) < 20% based on repeated extraction, derivatization and detection. The analytical accuracy for Populus leaf extracts, determined by a two-level spiking approach of selected metabolites, was 79-107%.

CONCLUSION

The results show the reliability of combined reversed phase liquid chromatography-tandem mass spectrometry for sugar phosphate analysis and demonstrate the presence of two unknown sugar phosphates in Populus extracts.

COI1-dependent jasmonate signalling affects growth, metabolite production and cell wall protein composition in arabidopsis

Background and Aims

Cultured cell suspensions have been the preferred model to study the apoplast as well as to monitor metabolic and cell cycle-related changes. Previous work showed that methyl jasmonate (MeJA) inhibits leaf growth in a CORONATINE INSENSITIVE 1 (COI1)-dependent manner, with COI1 being the jasmonate (JA) receptor. Here, the effect of COI1 overexpression on the growth of stably transformed arabidopsis cell cultures is described.

Methods

Time-course experiments were carried out to analyse gene expression, and protein and metabolite levels.

Key Results

Both MeJA treatment and the overexpression of COI1 modify growth, by altering cell proliferation and expansion. DNA content as well as transcript patterns of cell cycle and cell wall remodelling markers were altered. COI1 overexpression also increases the protein levels of OLIGOGALACTURONIDE OXIDASE 1, BETA-GLUCOSIDASE/ENDOGLUCANASES and POLYGALACTURONASE INHIBITING PROTEIN2, reinforcing the role of COI1 in mediating defence responses and highlighting a link between cell wall loosening and growth regulation. Moreover, changes in the levels of the primary metabolites alanine, serine and succinic acid of MeJA-treated Arabidopsis cell cultures were observed. In addition, COI1 overexpression positively affects the availability of metabolites such as β-alanine, threonic acid, putrescine, glucose and myo-inositol, thereby providing a connection between JA-inhibited growth and stress responses.

Conclusions

This study contributes to the understanding of the regulation of growth and the production of metabolic resources by JAs and COI1. This will have important implications in dissecting the complex relationships between hormonal and cell wall signalling in plants. The work also provides tools to uncover novel mechanisms co-ordinating cell division and post-mitotic cell expansion in the absence of organ developmental control.

A metabolomics and proteomics study of the Lactobacillus plantarum in the grass carp fermentation

Background

Lactobacillus plantarum, a versatile lactic acid-fermenting bacterium, isolated from the traditional pickles in Ningbo of China, was chosen for grass carp fermentation, which could also improve the flavor of grass carp. We here explored the central metabolic pathways of L. plantarum by using metabolomic approach, and further proved the potential for metabolomics combined with proteomics approaches for the basic research on the changes of metabolites and the corresponding fermentation mechanism of L. plantarum fermentation.

Results

This study provides a cellular material footprinting of more than 77 metabolites and 27 proteins in L. plantarum during the grass carp fermentation. Compared to control group, cells displayed higher levels of proteins associated with glycolysis and nucleotide synthesis, whereas increased levels of serine, ornithine, aspartic acid, 2-piperidinecarboxylic acid, and fumarate, along with decreased levels of alanine, glycine, threonine, tryptophan, and lysine.

Conclusions

Our results may provide a deeper understanding of L. plantarum fermentation mechanism based on metabolomics and proteomic analysis and facilitate future investigations into the characterization of L. plantarum during the grass carp fermentation.

Electronic supplementary material

The online version of this article (10.1186/s12866-018-1354-x) contains supplementary material, which is available to authorized users.

Metabolomics of Ndufs4-/- skeletal muscle: Adaptive mechanisms converge at the ubiquinone-cycle

Leigh syndrome is one of the most common childhood-onset neurometabolic disorders resulting from a primary oxidative phosphorylation dysfunction and affecting mostly brain tissues. Ndufs4^-/- mice have been widely used to study the neurological responses in this syndrome, however the reason why these animals do not display strong muscle involvement remains elusive. We combined biochemical strategies and multi-platform metabolomics to gain insight into the metabolism of both glycolytic (white quadriceps) and oxidative (soleus) skeletal muscles from Ndufs4^-/- mice. Enzyme assays confirmed severely reduced (80%) CI activity in both Ndufs4^-/- muscle types, compared to WTs. No significant alterations were evident in other respiratory chain enzyme activities; however, Ndufs4^-/- solei displayed moderate decreases in citrate synthase (12%) and CIII (18%) activities. Through hypothesis-generating metabolic profiling, we provide the first evidence of adaptive responses to CI dysfunction involving non-classical pathways fueling the ubiquinone (Q) cycle. We report a respective 48 and 34 discriminatory metabolites between Ndufs4^-/- and WT white quadriceps and soleus muscles, among which the most prominent alterations indicate the involvement of the glycerol-3-phosphate shuttle, electron transfer flavoprotein system, CII, and proline cycle in fueling the Q cycle. By restoring the electron flux to CIII via the Q cycle, these adaptive mechanisms could maintain adequate oxidative ATP production, despite CI deficiency. Taken together, our results shed light on the underlying pathogenic mechanisms of CI dysfunction in skeletal muscle. Upon further investigation, these pathways could provide novel targets for therapeutic intervention in CI deficiency and potentially lead to the development of new treatment strategies.

Quenching for Microalgal Metabolomics: A Case Study on the Unicellular Eukaryotic Green Alga Chlamydomonas reinhardtii

Capturing a valid snapshot of the metabolome requires rapid quenching of enzyme activities. This is a crucial step in order to halt the constant flux of metabolism and high turnover rate of metabolites. Quenching with cold aqueous methanol is treated as a gold standard so far, however, reliability of metabolomics data obtained is in question due to potential problems connected to leakage of intracellular metabolites. Therefore, we investigated the influence of various parameters such as quenching solvents, methanol concentration, inclusion of buffer additives, quenching time and solvent to sample ratio on intracellular metabolite leakage from Chlamydomonas reinhardtii. We measured the recovery of twelve metabolite classes using gas chromatography mass spectrometry (GC-MS) in all possible fractions and established mass balance to trace the fate of metabolites during quenching treatments. Our data demonstrate significant loss of intracellular metabolites with the use of the conventional 60% methanol, and that an increase in methanol concentration or quenching time also resulted in higher leakage. Inclusion of various buffer additives showed 70 mM HEPES (4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid) to be suitable. In summary, we recommend quenching with 60% aqueous methanol supplemented with 70 mM HEPES (−40 °C) at 1:1 sample to quenching solvent ratio, as it resulted in higher recoveries for intracellular metabolites with subsequent reduction in the metabolite leakage for all metabolite classes.

Comparison of sequential derivatization with concurrent methods for GC/MS-based metabolomics

The gas chromatography/mass spectrometry (GC/MS)-based metabolomics requires a two-step derivatization procedure consisting of oximation and silylation. However, due to the incomplete derivatization and degeneration of the metabolites, good repeatability is difficult to obtain during the batch derivatization, as the time between completing the derivatization process and GC analysis differs from sample to sample. In this research, we successfully obtained good repeatability for the peak areas of 52 selected metabolites by sequential derivatization and interval injection, in which the oximation and silylation times were maintained at constant values. In addition, the derivatization times and amount of reagents employed were varied to confirm that the optimal derivatization conditions differed for the various metabolites. In conventional batch derivatization, six metabolites, viz. glutamine, glutamic acid, histidine, alanine, asparagine, and tryptophan, exhibited fluctuations in their peak areas. Indeed, we found that for all six metabolites these differences originated from the silylation process, while the variations for glutamine and glutamic acid were related to the oximation process.

Strategies for large-scale targeted metabolomics quantification by liquid chromatography-mass spectrometry

Advances in liquid chromatography-mass spectrometry (LC-MS) instruments and analytical strategies have brought about great progress in targeted metabolomics analysis. This methodology is now capable of performing precise targeted measurement of dozens or hundreds of metabolites in complex biological samples. Classic targeted quantification assay using the multiple reaction monitoring (MRM) mode has been the foundation of high-quality metabolite quantitation. However, utilization of this strategy in biological studies has been limited by its relatively low metabolite coverage and throughput capacity. A number of methods for large-scale targeted metabolomics assay which have been developed overcome these limitations. These strategies have enabled extended metabolite coverage which is defined as targeting of large numbers of metabolites, while maintaining reliable quantification performance. These recently developed techniques thus bridge the gap between traditional targeted metabolite quantification and untargeted metabolomics profiling, and have proven to be powerful tools for metabolomics study. Although the LC-MRM-MS strategy has been used widely in large-scale metabolomics quantification analysis due to its fast scan speed and ideal analytic stability, there are still drawbacks which are due to the low resolution of the triple quadrupole instruments used for MRM assays. New approaches have been developed to expand the options for large-scale targeted metabolomics study, using high-resolution instruments such as parallel reaction monitoring (PRM). MRM and PRM-based techniques are now attractive strategies for quantitative metabolomics analysis and high-throughput biomarker discovery. Here we provide an overview of the major developments in LC-MS-based strategies for large-scale targeted metabolomics quantification in biological samples. The advantages of LC-MRM/PRM-MS based analytical strategies which may be used in multiplexed and high throughput quantitation for a wide range of metabolites are highlighted. In particular, PRM and MRM strategies are compared, and we summarize the work flow commonly used for large-scale targeted metabolomics analysis including sample preparation, LC separation and data analysis, as well as recent applications in biological studies.

Anaerobic nitrate reduction divergently governs population expansion of the enteropathogen Vibrio cholerae

To survive and proliferate in the absence of oxygen, many enteric pathogens can undergo anaerobic respiration within the host by using nitrate (NO₃^-) as electron acceptor ^1,2. In these bacteria, NO₃^- is typically reduced by a nitrate reductase to nitrite (NO₂^-), a toxic intermediate that is further reduced by a nitrite reductase³. However, Vibrio cholerae, the intestinal pathogen that causes cholera, lacks a nitrite reductase, leading to NO₂^- accumulation during nitrate reduction⁴. Thus, V. cholerae is thought to be unable to undergo NO₃^--dependent anaerobic respiration⁴. Here, we show that during hypoxic growth, NO₃^- reduction in V. cholerae divergently impacts bacterial fitness in a manner dependent on environmental pH. Remarkably, in alkaline conditions, V. cholerae can reduce NO₃^- to support population growth. Conversely, in acidic conditions, accumulation of NO₂^- from NO₃^- reduction simultaneously limits population expansion and preserves cell viability by lowering fermentative acid production. Interestingly, other bacterial species such as Salmonella typhimurium, enterohemorrhagic Escherichia coli (EHEC) and Citrobacter rodentium also reproduced this pH-dependent response suggesting that this mechanism might be conserved within enteric pathogens. Our findings explain how a bacterial pathogen can use a single redox reaction to divergently regulate population expansion depending on fluctuating environmental pH.

Acute sleep loss results in tissue-specific alterations in genome-wide DNA methylation state and metabolic fuel utilization in humans

Curtailed sleep promotes weight gain and loss of lean mass in humans, although the underlying molecular mechanisms are poorly understood. We investigated the genomic and physiological impact of acute sleep loss in peripheral tissues by obtaining adipose tissue and skeletal muscle after one night of sleep loss and after one full night of sleep. We find that acute sleep loss alters genome-wide DNA methylation in adipose tissue, and unbiased transcriptome-, protein-, and metabolite-level analyses also reveal highly tissue-specific changes that are partially reflected by altered metabolite levels in blood. We observe transcriptomic signatures of inflammation in both tissues following acute sleep loss, but changes involving the circadian clock are evident only in skeletal muscle, and we uncover molecular signatures suggestive of muscle breakdown that contrast with an anabolic adipose tissue signature. Our findings provide insight into how disruption of sleep and circadian rhythms may promote weight gain and sarcopenia.

Metabolic Profiling of Multiorgan Samples: Evaluation of MODY5/RCAD Mutant Mice

In the present study, we performed a metabolomics analysis to evaluate a MODY5/RCAD mouse mutant line as a potential model for HNF1B-associated diseases. Gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) of gut, kidney, liver, muscle, pancreas, and plasma samples uncovered the tissue specific metabolite distribution. Orthogonal projections to latent structures discriminant analysis (OPLS-DA) was used to identify the differences between MODY5/RCAD and wild-type mice in each of the tissues. The differences included, for example, increased levels of amino acids in the kidneys and reduced levels of fatty acids in the muscles of the MODY5/RCAD mice. Interestingly, campesterol was found in higher concentrations in the MODY5/RCAD mice, with a four-fold and three-fold increase in kidneys and pancreas, respectively. As expected, the MODY5/RCAD mice displayed signs of impaired renal function in addition to disturbed liver lipid metabolism, with increased lipid and fatty acid accumulation in the liver. From a metabolomics perspective, the MODY5/RCAD model was proven to display a metabolic pattern similar to what would be suspected in HNF1B-associated diseases. These findings were in line with the presumed outcome of the mutation based on the different anatomy and function of the tissues as well as the effect of the mutation on development.

Quantification of run order effect on chromatography - mass spectrometry profiling data

Chromatographic systems coupled with mass spectrometry detection are widely used in biological studies investigating how levels of biomolecules respond to different internal and external stimuli. Such changes are normally expected to be of low magnitude and therefore all experimental factors that can influence the analysis need to be understood and minimized. Run order effect is commonly observed and constitutes a major challenge in chromatography-mass spectrometry based profiling studies that needs to be addressed before the biological evaluation of measured data is made. So far there is no established consensus, metric or method that quickly estimates the size of this effect. In this paper we demonstrate how orthogonal projections to latent structures (OPLS®) can be used for objective quantification of the run order effect in profiling studies. The quantification metric is expressed as the amount of variation in the experimental data that is correlated to the run order. One of the primary advantages with this approach is that it provides a fast way of quantifying run-order effect for all detected features, not only internal standards. Results obtained from quantification of run order effect as provided by the OPLS can be used in the evaluation of data normalization, support the optimization of analytical protocols and identification of compounds highly influenced by instrumental drift. The application of OPLS for quantification of run order is demonstrated on experimental data from plasma profiling performed on three analytical platforms: GCMS metabolomics, LCMS metabolomics and LCMS lipidomics.

A freshwater diatom challenged by Zn: Biochemical, physiological and metabolomic responses of Tabellaria flocculosa(Roth) Kützing

Freshwater ecosystems are under threatening anthropogenic pressures worldwide, namely by metals. Diatoms are used as water quality indicators, but the influence of micronutrients such as Zn and its impacts are poorly understood. Thus, our study aimed to elucidate the tolerance level, the cellular targets and the responses to counteract Zn toxicity of freshwater diatoms by exposing Tabellaria flocculosa, isolated from a Zn contaminated stream. Biochemical, physiological and metabolomic approaches were used. It was demonstrated that Zn is toxic to T. flocculosa at concentrations occurring in contaminated environments. At low stress (30 μg Zn/L) few alterations in the metabolome were observed, but the enzymatic (SOD, CAT) and molecular (GSH, GSSG) antioxidant systems were induced, protecting cells from oxidative stress. At moderate stress (500 μg Zn/L) the main changes occurred in the metabolome (increases in fatty acids, amino acids, terpenoids, glycerol and phosphate, decreases in sucrose and lumichrome) with a moderate increase in cell damage (LPO and PC). The concerted action of all these mechanisms resulted in a non-significant decrease of growth, explaining the survival of this T. flocculosa strain in an environment with this Zn concentration. At the highest stress level (1000 μg Zn/L) the metabolome was identical to 500 μg Zn/L, and the induction of antioxidant systems and extracellular ion chelation (exopolysaccharides, frustulins) were the main responses to the increase of Zn toxicity. However, these mechanisms were unable to effectively abrogate cellular damage and growth reduction was observed. Moreover, the decrease in sucrose and especially in lumichrome should be tested as new specific markers of Zn toxicity. The information obtained in this study can assist in environmental risk assessment policies, support the prediction of diatom behaviour in highly impacted Zn environments, such as mining scenarios, and may help develop new indices, which include alterations induced by metals.

Assessing Cu impacts on freshwater diatoms: biochemical and metabolomic responses of Tabellaria flocculosa (Roth) Kützing

Metals are a recognised threat to aquatic organisms but the impact of metals such as copper (Cu) on benthic freshwater diatoms is poorly understood, even if diatoms are commonly used as water quality indicators. Our study aimed to elucidate the cellular targets of Cu toxicity and the mechanisms cells resort to counteract toxicity and to increase tolerance to Cu. A concerted approach analysing the biochemical, physiological and metabolome alterations in diatom cells was conducted by exposing the freshwater diatom Tabellaria flocculosa to 0, 0.3, 6 and 10μgCu/L. Cu was already toxic to T. flocculosa at concentrations common in environments and which are not usually considered to be contaminated (0.3μgCu/L). Under Cu impact, the metabolome of T. flocculosa changed significantly, especially at high concentrations (6 and 10μgCu/L). Cu toxicity was counteracted by increasing extracellular immobilization (EPS, frustulins), antioxidant (SOD, CAT) and detoxifying (GSTs) enzymes activity and low molecular weight antioxidants (GSH). These mechanisms were fuelled by higher energy production (increased ETS activity). At the highest Cu concentration (10μg/L), these processes were specially enhanced in an attempt to restrain the oxidative stress generated by high intracellular Cu concentrations. However, these mechanisms were not able to fully protect cells, and damage in membranes and proteins increased. Moreover, the decrease of hydroxylamine and unsaturated fatty acids and the increase of saturated fatty acids, 2-palmitoylglycerol, glycerol and diterpenoid compounds should be tested as new specific markers of Cu toxicity in future studies. This information can support the prediction of diatom behaviour in different Cu contamination levels, including highly impacted environments, such as mining scenarios, and may assist in environmental risk assessment policies and restoration programs.

Miniaturized 1H-NMR method for analyzing limited-quantity samples applied to a mouse model of Leigh disease

INTRODUCTION

The analysis of limited-quantity samples remains a challenge associated with mouse models, especially for multi-platform metabolomics studies. Although inherently insensitive, the highly specific characteristics of nuclear magnetic resonance (NMR) spectroscopy make it an advantageous platform for global metabolite profiling, particularly in mitochondrial disease research.

OBJECTIVES

Show method equivalency between a well-established standard operating protocol (SOP) and our novel miniaturized ¹H-NMR method.

METHOD

The miniaturized method was performed in a 2 mm NMR tube on a standard 500 MHz NMR spectrometer with a 5 mm triple-resonance inverse TXI probe at room temperature.

RESULTS

Firstly, using synthetic urine spiked with low (50 µM), medium (250 µM) and high (500 µM) levels (n = 10) of nine standards, both the SOP and miniaturized method were shown to have acceptable precision (CV < 15%), relative accuracy (80-120%), and linearity (R² > 0.95), except for taurine. Furthermore, statistical equivalence was shown using the two one-sided test. Secondly, pooled mouse quadriceps muscle extract was used to further confirm method equivalence (n = 3), as well as explore the analytical dynamics of this novel approach by analyzing more-concentrated versions of samples (up to 10× concentration) to expand identification of metabolites qualitatively, with quantitative linearity. Lastly, we demonstrate the new technique's application in a pilot metabolomics study using minute soleus muscle tissue from a mouse model of Leigh syndrome using Ndufs4 KO mice.

CONCLUSION

We demonstrate method equivalency, supporting our novel miniaturized ¹H-NMR method as a financially feasible alternative to cryoprobe technology-for limited-quantity biological samples in metabolomics studies that requires a volume one-tenth of the SOP.

Normalizing Gas-Chromatography-Mass Spectrometry Data: Method Choice can Alter Biological Inference

We demonstrate how different normalization techniques in GC-MS analysis impart unique properties to the data, influencing any biological inference. Using simulations, and empirical data, we compare the most commonly used techniques (Total Sum Normalization 'TSN'; Median Normalization 'MN'; Probabilistic Quotient Normalization 'PQN'; Internal Standard Normalization 'ISN'; External Standard Normalization 'ESN'; and a compositional data approach 'CODA'). When differences between biological classes are pronounced, ESN and ISN provides good results, but are less reliable for more subtly differentiated groups. MN, TSN, and CODA approaches produced variable results dependent on the structure of the data, and are prone to false positive biomarker identification. In contrast, PQN exhibits the lowest false positive rate, though with occasionally poor model performance. Because ESN requires extensive pre-planning, and offers only mixed reliability, and ISN, TSN, MN, and CODA approaches are prone to introducing artefactual differences, we recommend the use of PQN in GC-MS research.

NormalizeMets: assessing, selecting and implementing statistical methods for normalizing metabolomics data

INTRODUCTION

In metabolomics studies, unwanted variation inevitably arises from various sources. Normalization, that is the removal of unwanted variation, is an essential step in the statistical analysis of metabolomics data. However, metabolomics normalization is often considered an imprecise science due to the diverse sources of variation and the availability of a number of alternative strategies that may be implemented.

OBJECTIVES

We highlight the need for comparative evaluation of different normalization methods and present software strategies to help ease this task for both data-oriented and biological researchers.

METHODS

We present NormalizeMets-a joint graphical user interface within the familiar Microsoft Excel and freely-available R software for comparative evaluation of different normalization methods. The NormalizeMets R package along with the vignette describing the workflow can be downloaded from https://cran.r-project.org/web/packages/NormalizeMets/ . The Excel Interface and the Excel user guide are available on https://metabolomicstats.github.io/ExNormalizeMets .

RESULTS

NormalizeMets allows for comparative evaluation of normalization methods using criteria that depend on the given dataset and the ultimate research question. Hence it guides researchers to assess, select and implement a suitable normalization method using either the familiar Microsoft Excel and/or freely-available R software. In addition, the package can be used for visualisation of metabolomics data using interactive graphical displays and to obtain end statistical results for clustering, classification, biomarker identification adjusting for confounding variables, and correlation analysis.

CONCLUSION

NormalizeMets is designed for comparative evaluation of normalization methods, and can also be used to obtain end statistical results. The use of freely-available R software offers an attractive proposition for programming-oriented researchers, and the Excel interface offers a familiar alternative to most biological researchers. The package handles the data locally in the user's own computer allowing for reproducible code to be stored locally.

Glutamine-Elicited Secretion of Glucagon-Like Peptide 1 Is Governed by an Activated Glutamate Dehydrogenase

Glucagon-like peptide 1 (GLP-1), secreted from intestinal L cells, glucose dependently stimulates insulin secretion from β-cells. This glucose dependence prevents hypoglycemia, rendering GLP-1 analogs a useful and safe treatment modality in type 2 diabetes. Although the amino acid glutamine is a potent elicitor of GLP-1 secretion, the responsible mechanism remains unclear. We investigated how GLP-1 secretion is metabolically coupled in L cells (GLUTag) and in vivo in mice using the insulin-secreting cell line INS-1 832/13 as reference. A membrane-permeable glutamate analog (dimethylglutamate [DMG]), acting downstream of electrogenic transporters, elicited similar alterations in metabolism as glutamine in both cell lines. Both DMG and glutamine alone elicited GLP-1 secretion in GLUTag cells and in vivo, whereas activation of glutamate dehydrogenase (GDH) was required to stimulate insulin secretion from INS-1 832/13 cells. Pharmacological inhibition in vivo of GDH blocked secretion of GLP-1 in response to DMG. In conclusion, our results suggest that nonelectrogenic nutrient uptake and metabolism play an important role in L cell stimulus-secretion coupling. Metabolism of glutamine and related analogs by GDH in the L cell may explain why GLP-1 secretion, but not that of insulin, is activated by these secretagogues in vivo.

Dark period transcriptomic and metabolic profiling of two diverse Eutrema salsugineum accessions

Eutrema salsugineum is a model species for the study of plant adaptation to abiotic stresses. Two accessions of E. salsugineum, Shandong (SH) and Yukon (YK), exhibit contrasting morphology and biotic and abiotic stress tolerance. Transcriptome profiling and metabolic profiling from tissue samples collected during the dark period were used to investigate the molecular and metabolic bases of these contrasting phenotypes. RNA sequencing identified 17,888 expressed genes, of which 157 were not in the published reference genome, and 65 of which were detected for the first time. Differential expression was detected for only 31 genes. The RNA sequencing data contained 14,808 single nucleotide polymorphisms (SNPs) in transcripts, 3,925 of which are newly identified. Among the differentially expressed genes, there were no obvious candidates for the physiological or morphological differences between SH and YK. Metabolic profiling indicated that YK accumulates free fatty acids and long-chain fatty acid derivatives as compared to SH, whereas sugars are more abundant in SH. Metabolite levels suggest that carbohydrate and respiratory metabolism, including starch degradation, is more active during the first half of the dark period in SH. These metabolic differences may explain the greater biomass accumulation in YK over SH. The accumulation of 56% of the identified metabolites was lower in F1 hybrids than the mid-parent averages and the accumulation of 17% of the metabolites in F1 plants transgressed the level in both parents. Concentrations of several metabolites in F1 hybrids agree with previous studies and suggest a role for primary metabolism in heterosis. The improved annotation of the E. salsugineum genome and newly identified high-quality SNPs will permit accelerated studies using the standing variation in this species to elucidate the mechanisms of its diverse adaptations to the environment.

Single-platform ‘multi-omic’ profiling: unified mass spectrometry and computational workflows for integrative proteomics–metabolomics analysis

Advances in instrumentation and analysis tools are permitting evermore comprehensive interrogation of diverse biomolecules and allowing investigators to move from linear signaling cascades to network models, which more accurately reflect the molecular basis of biological systems and processes.

Changes in monosaccharides, organic acids and amino acids during Cabernet Sauvignon wine ageing based on a simultaneous analysis using gas chromatography-mass spectrometry

BACKGROUND

Monosaccharides, organic acids and amino acids are the important flavour-related components in wines. The aim of this article is to develop and validate a method that could simultaneously analyse these compounds in wine based on silylation derivatisation and gas chromatography-mass spectrometry (GC-MS), and apply this method to the investigation of the changes of these compounds and speculate upon their related influences on Cabernet Sauvignon wine flavour during wine ageing. This work presented a new approach for wine analysis and provided more information concerning red wine ageing.

RESULTS

This method could simultaneously quantitatively analyse 2 monosaccharides, 8 organic acids and 13 amino acids in wine. A validation experiment showed good linearity, sensitivity, reproducibility and recovery. Multiple derivatives of five amino acids have been found but their effects on quantitative analysis were negligible, except for methionine. The evolution pattern of each category was different, and we speculated that the corresponding mechanisms involving microorganism activities, physical interactions and chemical reactions had a great correlation with red wine flavours during ageing.

CONCLUSION

Simultaneously quantitative analysis of monosaccharides, organic acids and amino acids in wine was feasible and reliable and this method has extensive application prospects. © 2017 Society of Chemical Industry.

Characterization of an easy-to-use method for the routine analysis of the central metabolism using an affordable low-resolution GC-MS system: application to Arthrospira platensis

We developed an easy-to-use method for the routine analysis of the central metabolism using an affordable low-resolution GC-MS system run in SIM mode. The profiling approach was optimized for the derivatization protocol of some 60 targeted metabolites. The performance of two silylation reagents (MSTFA and BSTFA) that allowed the comprehensive derivatization of 42 key intermediary metabolites of the 60 initially targeted (organic acids, phosphate derivatives, monosaccharides and amino acids) was measured. The experimental results unequivocally showed that the MSTFA reagent met mandatory criteria including ease of handling (a very simple one-step protocol was developed), comprehensiveness of derivatization (the 42 compounds covered the extended metabolic pathways of the central carbon metabolism, with a coverage percentage ranging from 17% for the worst to 90% for the best result), optimized response coefficient of the whole derivatives (median value greater than the others by one order of magnitude) and repeatability of the protocol (RSD value below 25% for the whole procedure). When tested in real conditions (cyanobacteria polar extract), the experimental results showed that the profiling methodology was adequately repeatable (RSD = 35%) to ensure quantification results comparable with much more sensitive analytical techniques (capillary electrophoresis/mass spectrometry and liquid chromatography/triple quadrupole mass spectrometry system), while needing only about twice the quantity of biomass. Graphical abstract Schematic overview of an easy-to-use profiling method for the routine analysis of the central metabolism using a low-resolution GC-MS system.

Metabolome and transcriptome profiling reveal new insights into somatic embryo germination in Norway spruce (Picea abies)

Transcriptome, metabolome and histological profiling were performed on normal and aberrant somatic embryo germinants of Norway spruce (Picea abies L. Karst) providing a simplistic systems biology description of conifer germination. Aberrant germinants (AGs) formed periderm-like tissue at the apical pole and lacked shoot growth above the cotyledons. Transcriptome profiling (RNA-Sequencing) revealed a total of 370 differentially expressed genes at ≥1 or ≤-1 log2-fold change, where 92% were down-regulated in AGs compared with normal germinants (NGs). Genes associated with shoot apical meristem formation were down-regulated in AGs, or not differentially expressed between AGs and NGs. Genes involved in hormone signaling and transport were also down-regulated. Metabolite profiling by gas chromatography-mass spectrometry (MS) and liquid chromatography-MS revealed biochemical difference between AGs and NGs, notably increased levels of sugars including glucose in AGs. Genes involved in glucose signaling were down-regulated and genes involved in starch biosynthesis were up-regulated, suggesting involvement of sugar signaling during late embryo development and germination. The overall results provide new data enabling further studies to confirm potential markers for a normal germination process in conifers.