Metabolomics analysis II. Preparation of biological samples prior to detection

Amino acid-based ionic liquid surface modification of magnetic nanoparticles for the magnetic solid-phase extraction of heme proteins

Amino acid-based ionic liquid functionalized magnetic nanoparticles were fabricated as an MSPE adsorbent for hemoglobin with a binding capacity of 1.58 g g⁻¹.

Data Fusion in Metabolomics and Proteomics for Biomarker Discovery

Proteomics and metabolomics provide key insights into status and dynamics of biological systems. These molecular studies reveal the complex mechanisms involved in disease or aging processes. Invaluable information can be obtained using various analytical techniques such as nuclear magnetic resonance, liquid chromatography, or gas chromatography coupled to mass spectrometry. Each method has inherent advantages and drawbacks, but they are complementary in terms of biological information.The fusion of different measurements is a complex topic. We describe here a framework allowing combining multiple data sets, provided by different analytical platforms. For each platform, the relevant information is extracted in the first step. The obtained latent variables are then fused and further analyzed. The influence of the original variables is then calculated back and interpreted.

In Situ Analysis of Small Populations of Adherent Mammalian Cells Using Laser Ablation Electrospray Ionization Mass Spectrometry in Transmission Geometry

Most cultured cells used for biomedical research are cultured adherently, and the requisite detachment prior to biochemical analysis might induce chemical changes. This is especially crucial if accurate metabolic measurements are desired, given the rapid turnover of metabolites in living organisms. There are only a few methods available for the nontargeted in situ analysis of small adherent cell populations. Here we show that laser ablation electrospray ionization (LAESI) mass spectrometry (MS) can be used to analyze adherent cells directly, while still attached to the culture surface. To reduce the size of the analyzed cell population, the spot size constraints of conventional focusing in reflection geometry (rg) LAESI had to be eliminated. By introducing transmission geometry (tg) LAESI and incorporating an objective with a high numerical aperture, spot sizes of 10-20 μm were readily achieved. As few as five adherent cells could be specifically selected for analysis in their culturing environment. The importance of in situ analysis was highlighted by comparing the metabolite composition of adherent versus suspended cells. For example, we observed that cells analyzed adherently yielded higher values for the adenylate energy charge (0.90 ± 0.09 for adherent cells vs 0.09 ± 0.03 for suspended cells). Additionally, due to the smaller focal spot size, tg-LAESI enabled the analysis of ∼20 times smaller cell populations compared to rg-LAESI.

Development of high throughput 96-blade solid phase microextraction-liquid chromatrography-mass spectrometry protocol for metabolomics

In metabolomics, the workflow for quantitative and comprehensive metabolic mapping of cellular metabolites can be a very challenging undertaking. Sampling and sample preparation play a significant role in untargeted analysis, as they may affect the composition of the analyzed metabolome. In the current work, different solid phase microextraction (SPME) coating chemistries were developed and applied to provide simultaneous extraction of a wide range of both hydrophobic and hydrophilic cellular metabolites produced by a model organism, Escherichia coli. Three different LC-MS methods were also evaluated for analysis of extracted metabolites. Finally, over 200 cellular metabolites were separated and detected with widely varying hydrophobicities ranging within -7 < log P < 15, including amino acids, peptides, nucleotides, carbohydrates, polycarboxylic acids, vitamins, phosphorylated compounds, and lipids such as hydrophobic phospholipids, prenol lipids, and fatty acids at the stationary phase of the E. coli life cycle using the developed 96-blade SPME-LC-MS method.

Comparison of Two Different Astragali Radix by a ¹H NMR-Based Metabolomic Approach

Astragali Radix (AR) is a commonly used herbal drug in traditional chinese medicine and is widely used for the treatment of diabetes, cardiovascular diseases, nephropathy, and neuropathy. The main source of AR in China is the dried root of Astragalus membranaceus var. mongholicus (Bge.) Hsiao, and both cultivated and wild ARs are used clinically. A systematic comparison of cultivated AR (GS-AR) and wild AR (SX-AR) should be performed to ensure the clinical efficacy and safety. In this study, the chemical composition of the two different ARs, which were collected in the Shanxi (wild) and Gansu (cultivated) provinces, were compared by NMR-based metabolic fingerprint coupled with multivariate analysis. The SX-AR- and GS-AR-induced metabolic changes in the endogenous metabolites in mice were also compared. The results showed that SX-AR and GS-AR differed significantly not only in the primary metabolites but also in the secondary metabolites. However, alterations among the endogenous metabolites in the serum, lung, liver, and spleen were relatively small. This study provided a novel and valuable method for the evaluation of the consistency and diversity of herbal drugs, and further studies should be conducted on the difference in polysaccharides as well as the biological effects between the two kinds of AR.

Potential of mass spectrometry metabolomics for chemical food safety

This review aims to describe the most significant applications of mass spectrometry-based metabolomics in the field of chemical food safety. A particular discussion of all the different analytical steps involved in the metabolomics workflow (sample preparation, mass spectrometry analytical platform and data processing) will be addressed.

Controllable construction of micro/nanostructured NiO arrays in confined microchannels via microfluidic chemical fabrication for highly efficient and specific absorption of abundant proteins

The multiple micro/nanostructured NiO arrays constructed on the inner walls of the microchannels via a simple microfluidic chemical method exhibit highly efficient and specific absorption of abundant proteins.

Metabolism in chronic fatigue syndrome

Chronic fatigue syndrome (CFS) is a poorly understood condition that presents as long-term physical and mental fatigue with associated symptoms of pain and sensitivity across a broad range of systems in the body. The poor understanding of the disorder comes from the varying clinical diagnostic definitions as well as the broad array of body systems from which its symptoms present. Studies on metabolism and CFS suggest irregularities in energy metabolism, amino acid metabolism, nucleotide metabolism, nitrogen metabolism, hormone metabolism, and oxidative stress metabolism. The overwhelming body of evidence suggests an oxidative environment with the minimal utilization of mitochondria for efficient energy production. This is coupled with a reduced excretion of amino acids and nitrogen in general. Metabolomics is a developing field that studies metabolism within a living system under varying conditions of stimuli. Through its development, there has been the optimisation of techniques to do large-scale hypothesis-generating untargeted studies as well as hypothesis-testing targeted studies. These techniques are introduced and show an important future direction for research into complex illnesses such as CFS.

Basics of mass spectrometry based metabolomics

The emerging field of metabolomics, aiming to characterize small molecule metabolites present in biological systems, promises immense potential for different areas such as medicine, environmental sciences, agronomy, etc. The purpose of this article is to guide the reader through the history of the field, then through the main steps of the metabolomics workflow, from study design to structure elucidation, and help the reader to understand the key phases of a metabolomics investigation and the rationale underlying the protocols and techniques used. This article is not intended to give standard operating procedures as several papers related to this topic were already provided, but is designed as a tutorial aiming to help beginners understand the concept and challenges of MS-based metabolomics. A real case example is taken from the literature to illustrate the application of the metabolomics approach in the field of doping analysis. Challenges and limitations of the approach are then discussed along with future directions in research to cope with these limitations. This tutorial is part of the International Proteomics Tutorial Programme (IPTP18).

Evaluation of horse urine sample preparation methods for metabolomics using LC coupled to HRMS

Background: Horse urine is the medium of choice for the implementation of metabolomic approaches aimed at improving horse doping control. However, drug analysis in this biofluid is a challenging task due to the presence of large amounts of interfering compounds. Methodology & Results: A comparative study of sample preparation has been conducted to evaluate five sample-preparation methods, namely acetonitrile precipitation, proteinase K hydrolysis, membrane filtration and sample dilution with water by factors of five and 20, for metabolome analysis using liquid chromatography coupled to high resolution mass spectrometry. Assessment was performed at both global and targeted levels, by using a few thousand features obtained from peak detection software, and internal standards and 100 annotated or identified metabolites. Conclusion: By considering the number of detected signals, their intensity and their detection repeatability, acetonitrile precipitation was selected as the most efficient sample-preparation method for the analysis of horse urine metabolome in liquid chromatography coupled to high resolution mass spectrometry conditions.

Potential input from metabolomics for exploring and understanding the links between environment and health

Humans may be exposed via their environment to multiple chemicals as a consequence of human activities and use of synthetic products. Little knowledge is routinely generated on the hazards of these chemical mixtures. The metabolomic approach is widely used to identify metabolic pathways modified by diseases, drugs, or exposures to toxicants. This review, based on the state of the art of the current applications of metabolomics in environmental health, attempts to determine whether metabolomics might constitute an original approach to the study of associations between multiple, low-dose environmental exposures in humans. Studying the biochemical consequences of complex environmental exposures is a challenge demanding the development of careful experimental and epidemiological designs, in order to take into account possible confounders associated with the high level of interindividual variability induced by different lifestyles. The choices of populations studied, sampling and storage procedures, statistical tools used, and system biology need to be considered. Suggestions for improved experimental and epidemiological designs are described. Evidence indicates that metabolomics may be a powerful tool in environmental health in the identification of both complex exposure biomarkers directly in human populations and modified metabolic pathways, in an attempt to improve understanding the underlying environmental causes of diseases. Nevertheless, the validity of biomarkers and relevancy of animal-to-human extrapolation remain key challenges that need to be properly explored.

Methods of discovery-based and targeted metabolite analysis by comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry detection

The investigation of naturally volatile and derivatized metabolites in biological tissues by comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC × GC-TOFMS) can provide highly complex and information-rich data for comprehensive metabolomics analysis. The addition of the second separation dimension with GC × GC provides additional chemical selectivity, and the fast scanning time of TOFMS offers benefits in chemical selectivity and overall peak capacity compared to traditional one-dimensional (1D) GC. Furthermore, methods of derivatization to facilitate volatility and thermal stability, the most prominent being the silylation of organic compounds, have extended the use of GC as an important metabolomics tool. The highly information-rich data from GC × GC-TOFMS benefits from sophisticated comprehensive targeted and nontargeted algorithmic software methods. Herein, we detail a robust derivatization and instrumental method for metabolomics analysis and provide a brief overview of possible methods for data analysis.

Toward 'omic scale metabolite profiling: a dual separation-mass spectrometry approach for coverage of lipid and central carbon metabolism

Although the objective of any 'omic science is broad measurement of its constituents, such coverage has been challenging in metabolomics because the metabolome is comprised of a chemically diverse set of small molecules with variable physical properties. While extensive studies have been performed to identify metabolite isolation and separation methods, these strategies introduce bias toward lipophilic or water-soluble metabolites depending on whether reversed-phase (RP) or hydrophilic interaction liquid chromatography (HILIC) is used, respectively. Here we extend our consideration of metabolome isolation and separation procedures to integrate RPLC/MS and HILIC/MS profiling. An aminopropyl-based HILIC/MS method was optimized on the basis of mobile-phase additives and pH, followed by evaluation of reproducibility. When applied to the untargeted study of perturbed bacterial metabolomes, the HILIC method enabled the accurate assessment of key, dysregulated metabolites in central carbon pathways (e.g., amino acids, organic acids, phosphorylated sugars, energy currency metabolites), which could not be retained by RPLC. To demonstrate the value of the integrative approach, bacterial cells, human plasma, and cancer cells were analyzed by combined RPLC/HILIC separation coupled to ESI positive/negative MS detection. The combined approach resulted in the observation of metabolites associated with lipid and central carbon metabolism from a single biological extract, using 80% organic solvent (ACN:MeOH:H2O 2:2:1). It enabled the detection of more than 30,000 features from each sample type, with the highest number of uniquely detected features by RPLC in ESI positive mode and by HILIC in ESI negative mode. Therefore, we conclude that when time and sample are limited, the maximum amount of biological information related to lipid and central carbon metabolism can be acquired by combining RPLC ESI positive and HILIC ESI negative mode analysis.

Mammalian cell metabolomics: experimental design and sample preparation

Metabolomics represents the global assessment of metabolites in a biological sample and reports the closest information to the phenotype of the biological system under study. Mammalian cell metabolomics has emerged as a promising tool with potential applications in many biotechnology and research areas. Metabolomics workflow includes experimental design, sampling, sample processing, metabolite analysis, and data processing. Given their influence on metabolite content and biological interpretation of data, a good experimental design and the appropriate choice of a sample processing method are prerequisites for success in any metabolomic study. The use of mammalian cells in the metabolomics field involves harder sample processing methods, including metabolism quenching and metabolite extraction, as compared to the use of body fluids, although such critical issues are frequently overlooked. This review aims to overview the common experimental procedures used in mammalian cell metabolomics based on mass spectrometry, by placing special emphasis on discussing sample preparation approaches, although other aspects, such as cell metabolomics applications, culture systems, cellular models, analytical platforms, and data analysis, are also briefly covered. This review intends to be a helpful tool to assist researchers in addressing decisions when planning a metabolomics study involving the use of mammalian cells.

Metabolic profiling of plasma from cardiac surgical patients concurrently administered with tranexamic acid: DI-SPME-LC-MS analysis

A metabolic profile of plasma samples from patients undergoing heart surgery with the use of cardiopulmonary bypass (CPB) and concurrent administration of tranexamic acid was determined. Direct immersion solid phase microextraction (DI-SPME), a new sampling and sample preparation tool for metabolomics, was used in this study for the first time to investigate clinical samples. The results showed alteration of diverse compounds involved in different biochemical pathways. The most significant contribution in changes induced by surgery and applied pharmacotherapy was noticed in metabolic profile of lysophospholipids, triacylglycerols, mediators of platelet aggregation, and linoleic acid metabolites. Two cases of individual response to treatment were also reported.

Combining small-volume metabolomic and transcriptomic approaches for assessing brain chemistry

The integration of disparate data types provides a more complete picture of complex biological systems. Here we combine small-volume metabolomic and transcriptomic platforms to determine subtle chemical changes and to link metabolites and genes to biochemical pathways. Capillary electrophoresis–mass spectrometry (CE–MS) and whole-genome gene expression arrays, aided by integrative pathway analysis, were utilized to survey metabolomic/transcriptomic hippocampal neurochemistry. We measured changes in individual hippocampi from the mast cell mutant mouse strain, C57BL/6 Kit^W-sh/W-sh. These mice have a naturally occurring mutation in the white spotting locus that causes reduced c-Kit receptor expression and an inability of mast cells to differentiate from their hematopoietic progenitors. Compared with their littermates, the mast cell-deficient mice have profound deficits in spatial learning, memory, and neurogenesis. A total of 18 distinct metabolites were identified in the hippocampus that discriminated between the C57BL/6 Kit^W-sh/W-sh and control mice. The combined analysis of metabolite and gene expression changes revealed a number of altered pathways. Importantly, results from both platforms indicated that multiple pathways are impacted, including amino acid metabolism, increasing the confidence in each approach. Because the CE–MS and expression profiling are both amenable to small-volume analysis, this integrated analysis is applicable to a range of volume-limited biological systems.

Computational tools for the secondary analysis of metabolomics experiments

Metabolomics experiments have become commonplace in a wide variety of disciplines. By identifying and quantifying metabolites researchers can achieve a systems level understanding of metabolism. These studies produce vast swaths of data which are often only lightly interpreted due to the overwhelmingly large amount of variables that are measured. Recently, a number of computational tools have been developed which enable much deeper analysis of metabolomics data. These data have been difficult to interpret as understanding the connections between dozens of altered metabolites has often relied on the biochemical knowledge of researchers and their speculations. Modern biochemical databases provide information about the interconnectivity of metabolism which can be automatically polled using metabolomics secondary analysis tools. Starting with lists of altered metabolites, there are two main types of analysis: enrichment analysis computes which metabolic pathways have been significantly altered whereas metabolite mapping contextualizes the abundances and significances of measured metabolites into network visualizations. Many different tools have been developed for one or both of these applications. In this review the functionality and use of these software is discussed. Together these novel secondary analysis tools will enable metabolomics researchers to plumb the depths of their data and produce farther reaching biological conclusions than ever before.

Novel methodologies in metabolic profiling with a focus on molecular diagnostic applications

The metabolome contains all the biological end points of genomic, transcriptomic and proteomic perturbations, also including the influence of gut microbiota and the environment, giving a direct picture of an organism's ongoing metabolic state. Metabolomics thus has the potential to be an effective tool for early diagnosis of disease, and also to be a predictor of treatment response and survival. In recent years, the development of instrumental systems has enabled more comprehensive coverage of the metabolome. Advances in mass spectrometry and chromatography have particularly improved both the efficiency of nontargeted metabolic profiling as well as the sensitivity and reliability of targeted analyses. Mass spectrometric techniques are also increasingly becoming accepted as a routine diagnostic tool in clinical laboratories. This review summarizes the most recent advances and current challenges in metabolomics, with a focus on mass spectrometric methods utilized in biomarker research, highlighted with selected examples.

Click chemistry: a new facile and efficient strategy for the preparation of Fe3O4 nanoparticles covalently functionalized with IDA-Cu and their application in the depletion of abundant protein in blood samples

In this study, we report a novel method to synthesize core-shell structured Fe(3)O(4) nanoparticles (NPs) covalently functionalized with iminodiacetic acid (IDA) via click chemistry between the azide and alkyne groups and charged with Cu(2+). Firstly, the Fe(3)O(4)@SiO(2) NPs were obtained using tetraethoxysilane (TEOS) to form a silica shell on the surface of the Fe(3)O(4) core. The azide group-modified Fe(3)O(4)@SiO(2) NPs were obtained by a sol-gel process using 3-azidopropyltriethoxysilane (AzPTES) as the silane agent. Fe(3)O(4)@SiO(2)-N(3) was directly reacted with N-propargyl iminodiacetic via click chemistry, in the presence of a Cu(I) catalyst, to acquire the IDA-modified Fe(3)O(4) NPs. Finally, through the addition of Cu(2+), the Fe(3)O(4)@SiO(2)-IDA-Cu NP product was obtained. The morphology, structure and composition of the NPs were characterized by transmission electron microscopy (TEM), X-ray powder diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy and X-ray photoelectron spectroscopy (XPS). The resulting NPs showed a strong magnetic response to an externally applied magnetic field, a high adsorption capacity and excellent specificity towards hemoglobin (Hb). In addition, the Fe(3)O(4)@SiO(2)-IDA-Cu NPs can be used for the selective removal of abundant Hb protein in bovine and human blood samples.

Optimization of cold methanol quenching for quantitative metabolomics of Penicillium chrysogenum

A sampling procedure for quantitative metabolomics in Penicillium chrysogenum based on cold aqueous methanol quenching was re-evaluated and optimized to reduce metabolite leakage during sample treatment. The optimization study included amino acids and intermediates of the glycolysis and the TCA-cycle. Metabolite leakage was found to be minimal for a methanol content of the quenching solution (QS) of 40% (v/v) while keeping the temperature of the quenched sample near -20°C. The average metabolite recovery under these conditions was 95.7% (±1.1%). Several observations support the hypothesis that metabolite leakage from quenched mycelia of P. chrysogenum occurs by diffusion over the cell membrane. First, a prolonged contact time between mycelia and the QS lead to a somewhat higher extent of leakage. Second, when suboptimal quenching liquids were used, increased metabolite leakage was found to be correlated with lower molecular weight and with lower absolute net charge. The finding that lowering the methanol content of the quenching liquid reduces metabolite leakage in P. chrysogenum contrasts with recently published quenching studies for two other eukaryotic micro-organisms. This demonstrates that it is necessary to validate and, if needed, optimize the quenching conditions for each particular micro-organism. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0367-3) contains supplementary material, which is available to authorized users.

Optimizing high-throughput metabolomic biomarker screening: a study of quenching solutions to freeze intracellular metabolism in CHO cells

Metabolomics is a rapidly emerging tool for studying and optimizing both media and bioprocess development for culturing recombinant mammalian cells that are used in protein production processes. Quenching of the cells is crucial to fix their metabolic status at the time of sampling. Three precooled quenching solutions were tested for their ability to fix the metabolic activity of CHO cells: phosphate-buffered saline (PBS) (pH 7.4; 0.5°C), 60% methanol with 70 mM HEPES (pH 7.4; -20°C), and 60% methanol with 0.85% (w/v) ammonium bicarbonate (AMBIC) (pH 7.4; -20°C). The metabolic activity of the sampled CHO cells was assessed by determining the intracellular levels of ATP using a bioluminescence assay and selected metabolites with LC-MS/MS. We found the precooled PBS (pH 7.4; 0.5°C) to be the optimal quenching reagent for fixing intracellular metabolism. Importantly, the structural integrity of the cell membrane was maintained and highest yields were obtained for intracellular levels of ATP as well as for 18 out of 28 intracellular metabolites. In contrast to the previously reported studies, buffered methanol quenching was not applicable for suspension cultured CHO cells as cellular membrane integrity was affected. We recommend that the cells are quenched and washed simultaneously to keep the sampling time to a minimum and to prevent any further metabolic activity in the cells. We observed that additional washing steps are not required. Our analyses suggest that methanol as quenching solution, even in combination with a buffer substance, appears not suitable for quenching sensitive mammalian cells. The protocol we report herein is a simple cell sampling method that enables high-throughput metabolomic analyses and is suitable for a large number of samples.

Establishment and application of a metabolomics workflow for identification and profiling of volatiles from leaves of Vitis vinifera by HS-SPME-GC-MS

INTRODUCTION

Volatile organic compounds (VOCs) occurring in leaves of plants carry information about the physiological state of the plant. Monitoring of VOCs assists in detecting plant stress before visible signs are present.

OBJECTIVE

To establish and apply a simple workflow for the automated extraction, measurement and annotation/identification of Vitis vinifera cv. Pinot Noir leaf metabolites.

METHODOLOGY

Leaf samples were harvested, cooled with liquid nitrogen and homogenised under cooled conditions. VOCs were extracted and enriched by solid phase microextraction (SPME) and analysed by GC-MS. Samples were measured on two columns with different polarity of stationary phases. Mass spectral deconvolution and identification was done by AMDIS software. Strict identification criteria were applied: match factor ≥ 90; relative retention index deviation ≤ 2% from reference value on both columns. Data of two sampling dates were analysed with multivariate statistics.

RESULTS

We found ~600 components in a single chromatogram. Applying the mentioned criteria resulted in annotation of 63 metabolites of which 47 were confirmed with authentic standards. For the majority of the compounds technical variability was < < 40% (RSD), biological variability among plants was 7-119%. Principal component analysis (PCA) scores plot of leaf samples from two different sampling dates showed two clearly separated clusters. The presented workflow enabled for the first time the detection and identification of 19 metabolites that have so far not been described for Vitis spp.

CONCLUSION

The developed workflow enabled the identification of grapevine leaf metabolites, which allowed the separation of leaves from two sampling dates by PCA.

Current trends and challenges in sample preparation for global metabolomics using liquid chromatography-mass spectrometry

The choice of sample-preparation method is extremely important in metabolomic studies because it affects both the observed metabolite content and biological interpretation of the data. An ideal sample-preparation method for global metabolomics should (i) be as non-selective as possible to ensure adequate depth of metabolite coverage; (ii) be simple and fast to prevent metabolite loss and/or degradation during the preparation procedure and enable high-throughput; (iii) be reproducible; and (iv) incorporate a metabolism-quenching step to represent true metabolome composition at the time of sampling. Despite its importance, sample preparation is often an overlooked aspect of metabolomics, so the focus of this review is to explore the role, challenges, and trends in sample preparation specifically within the context of global metabolomics by liquid chromatography-mass spectrometry (LC-MS). This review will cover the most common methods including solvent precipitation and extraction, solid-phase extraction and ultrafiltration, and discuss how to improve analytical quality and metabolite coverage in metabolomic studies of biofluids, tissues, and mammalian cells. Recent developments in this field will also be critically examined, including in vivo methods, turbulent-flow chromatography, and dried blood spot sampling.

LC-MS-based metabolomics

Metabolomics aims at identification and quantitation of small molecules involved in metabolic reactions. LC-MS has enjoyed a growing popularity as the platform for metabolomic studies due to its high throughput, soft ionization, and good coverage of metabolites. The success of a LC-MS-based metabolomic study often depends on multiple experimental, analytical, and computational steps. This review presents a workflow of a typical LC-MS-based metabolomic analysis for identification and quantitation of metabolites indicative of biological/environmental perturbations. Challenges and current solutions in each step of the workflow are reviewed. The review intends to help investigators understand the challenges in metabolomic studies and to determine appropriate experimental, analytical, and computational methods to address these challenges.

Development of quenching and washing protocols for quantitative intracellular metabolite analysis of uninfected and baculovirus-infected insect cells

Metabolomics refer to the global analysis of small molecule metabolites in a biological system, and can be a powerful tool to elucidate and optimize cellular processes, particularly when integrated into a systems biology framework. Determining the endometabolome in cultured animal cells is especially challenging, due to the conflicting demands for rapid quenching of metabolism and retention of membrane integrity, while cells are separated from the complex medium. The challenge is magnified in virus infected cells due to increased membrane fragility. This paper describes an effective methodology for quantitative intracellular metabolite analysis of the baculovirus-insect cell expression system, an important platform for the production of heterologous proteins and baculovirus-based biopesticides. These two applications were represented by Spodoptera frugiperda (Sf9) and Helicoverpa zea (HzAM1) cells infected with recombinant Autographa californica and wild-type Helicoverpa armigera nucleopolyhedroviruses (AcMNPV and HaSNPV), respectively. Specifically, an ice-cold quenching solution comprising 1.1% w/v NaCl and 0.2% w/v Pluronic® F-68 (NaCl+P) was found to be efficacious in preserving cell viability and minimizing cell leakage during quenching and centrifugation-based washing procedures (prior to extraction using cold 50% v/v acetonitrile). Good recoveries of intracellular adenosine triphosphate, total adenosine phosphates and amino acids were obtained after just one wash step, for both uninfected and infected insect cells. The ability to implement wash steps is critical, as insect cell media are metabolites-rich, while infected insect cells are much more fragile than their uninfected counterparts. Hence, a promising methodology has been developed to facilitate endometabolomic analysis of insect cell-baculovirus systems for bioprocess optimization.

Metabolomics and its application to studying metal toxicity

Here we explain the omics approach of metabolomics and how it can be applied to study a physiological response to toxic metal exposure. This review aims to educate the metallomics field to the tool of metabolomics. Metabolomics is becoming an increasingly used tool to compare natural and challenged states of various organisms, from disease states in humans to toxin exposure to environmental systems. This approach is key to understanding and identifying the cellular or biochemical targets of metals and the underlying physiological response. Metabolomics steps are described and overviews of its application to metal toxicity to organisms are given. As this approach is very new there are yet only a small number of total studies and therefore only a brief overview of some metal metabolomics studies is described. A frank critical evaluation of the approach is given to provide newcomers to the method a clear idea of the challenges and the rewards of applying metabolomics to their research.

Standard operation protocol for analysis of lipid hydroperoxides in human serum using a fully automated method based on solid-phase extraction and liquid chromatography-mass spectrometry in selected reaction monitoring

Standard operating procedures (SOPs) are of paramount importance in the analytical field to ensure the reproducibility of the results obtained among laboratories. SOPs gain special interest when the aim is the analysis of potentially unstable compounds. An SOP for analysis of lipid hydroperoxides (HpETEs) is here reported after optimization of the critical steps to be considered in their analysis in human serum from sampling to final analysis. The method is based on automated hyphenation between solid-phase extraction (SPE) and liquid chromatography-mass spectrometry (LC-MS). The developed research involves: (i) optimization of the SPE and LC-MS steps with a proper synchronization; (ii) validation of the method-viz. accuracy study (estimated as 86.4% as minimum value), evaluation of sensitivity and precision, which ranged from 2.5 to 7.0 ng/mL (0.25-0.70 ng on column) as quantification limit and precision below 13.2%), and robustness study (reusability of the cartridge for 5 times without affecting the accuracy and precision of the method); (iii) stability study, involving freeze-thaw stability, short-term and long-term stability and stock solution stability tests. The results thus obtained allow minimizing both random and systematic variation of the metabolic profiles of the target compounds by correct application of the established protocol.