Metabolic profiling of ultrasmall sample volumes with GC/MS: from microliter to nanoliter samples

Opportunities and challenges for sample preparation and enrichment in mass spectrometry for single-cell metabolomics

Single-cell heterogeneity in metabolism, drug resistance and disease type poses the need for analytical techniques for single-cell analysis. As the metabolome provides the closest view of the status quo in the cell, studying the metabolome at single-cell resolution may unravel said heterogeneity. A challenge in single-cell metabolome analysis is that metabolites cannot be amplified, so one needs to deal with picolitre volumes and a wide range of analyte concentrations. Due to high sensitivity and resolution, MS is preferred in single-cell metabolomics. Large numbers of cells need to be analysed for proper statistics; this requires high-throughput analysis, and hence automation of the analytical workflow. Significant advances in (micro)sampling methods, CE and ion mobility spectrometry have been made, some of which have been applied in high-throughput analyses. Microfluidics has enabled an automation of cell picking and metabolite extraction; image recognition has enabled automated cell identification. Many techniques have been used for data analysis, varying from conventional techniques to novel combinations of advanced chemometric approaches. Steps have been set in making data more findable, accessible, interoperable and reusable, but significant opportunities for improvement remain. Herein, advances in single-cell analysis workflows and data analysis are discussed, and recommendations are made based on the experimental goal.

A Sensitive GC-MS Method for Quantitation of Lipid A Backbone Components and Terminal Phosphate Modifications

Lipid A, the hydrophobic anchor of lipopolysaccharide (LPS) present in the outer membrane of Gram-negative bacteria, serves as a target for cationic antimicrobial peptides, such as polymyxins. Membrane stress from polymyxins results in activation of two-component regulatory systems that produce lipid A modifying enzymes. These enzymes add neutral moieties, such as aminoarabinose (AraN) and ethanolamine (EtN) to lipid A terminal phosphates that mask the phosphate's negative charge and inhibit electrostatic interaction with the cationic polymyxins. Currently, these modifications may be detected by MALDI-TOF MS; however, this analysis is only semiquantitative. Herein we describe a GC-MS method to quantitate lipid A backbone components, glucosamine (GlcN) and inorganic phosphate (Pi), along with terminal phosphate modifications AraN and EtN. In this assay, lipid A is isolated from Gram-negative bacterial samples, hydrolyzed into its individual moieties, and derivatized via methoximation followed by silylation prior to analysis via GC-MS. Changes in AraN and EtN quantity were characterized using a variety of regulatory mutants of Salmonella, revealing differences that were not detected using MALDI-TOF MS analysis. Additionally, an increase in the abundance of AraN and EtN modifications were observed when resistant Enterobacter and Escherichia coli strains were grown in the presence of colistin (polymyxin E). Lastly, increased levels of Pi were found in bisphosphorylated lipid A compared to monophosphorylated lipid A samples. Because lipid A modifications serve as indicators of polymyxin resistance in Gram-negative bacteria, this method provides the capacity to monitor polymyxin resistance by quantification of lipid A modification using GC-MS.

Combined metabolic analyses for the biosynthesis pathway of l-threonine in Escherichia coli

Currently, industrial production of l-threonine (Thr) is based on direct fermentation with microorganisms such as Escherichia coli, which has the characteristics of low cost and high productivity. In order to elucidate the key metabolic features of the synthesis pathway of Thr in E. coli to provide clues for metabolic regulation or engineering of the strain, this study was carried out on an l-threonine over-producing strain, in terms of analyses of metabolic flux, enzyme control and metabonomics. Since environmental disturbance and genetic modification are considered to be two important methods of metabolic analysis, addition of phosphate in the media and comparison of strains with different genotypes were selected as the two candidates due to their significant influence in the biosynthesis of Thr. Some important targets including key nodes, enzymes and biomarkers were identified, which may provide target sites for rational design through engineering the Thrproducing strain. Finally, metabolic regulation aimed at one biomarker identified in this study was set as an example, which confirms that combined metabolic analyses may guide to improve the production of threonine in E. coli.

Metabolic Profiling and Quantitative Analysis of Cerebrospinal Fluid Using Gas Chromatography-Mass Spectrometry: Current Methods and Future Perspectives

Cerebrospinal fluid is a key biological fluid for the investigation of new potential biomarkers of central nervous system diseases. Gas chromatography coupled to mass-selective detectors can be used for this investigation at the stages of metabolic profiling and method development. Different sample preparation conditions, including extraction and derivatization, can be applied for the analysis of the most of low-molecular-weight compounds of the cerebrospinal fluid, including metabolites of tryptophan, arachidonic acid, glucose; amino, polyunsaturated fatty and other organic acids; neuroactive steroids; drugs; and toxic metabolites. The literature data analysis revealed the absence of fully validated methods for cerebrospinal fluid analysis, and it presents opportunities for scientists to develop and validate analytical protocols using modern sample preparation techniques, such as microextraction by packed sorbent, dispersive liquid-liquid microextraction, and other potentially applicable techniques.

A GC-MS/Single-Cell Method to Evaluate Membrane Transporter Substrate Specificity and Signaling

Amino acid transporters play a vital role in metabolism and nutrient signaling pathways. Typically, transport activity is investigated using single substrates and competing amounts of other amino acids. We used GC-MS and LC-MS for metabolic screening of Xenopus laevis oocytes expressing various human amino acid transporters incubated in complex media to establish their comprehensive substrate profiles. For most transporters, amino acid selectivity matched reported substrate profiles. However, we could not detect substantial accumulation of cationic amino acids by SNAT4 and ATB0,+ in contrast to previous reports. In addition, comparative substrate profiles of two related sodium neutral amino acid transporters known as SNAT1 and SNAT2, revealed the latter as a significant leucine accumulator. As a consequence, SNAT2, but not SNAT1, was shown to be an effective activator of the eukaryotic cellular growth regulator mTORC1. We propose, that metabolomic profiling of membrane transporters in Xe nopus laevis oocytes can be used to test their substrate specificity and role in intracellular signaling pathways.

Analysis of low-molecular-weight metabolites in stomach cancer cells by a simplified and inexpensive GC/MS metabolomics method

GC/MS coupled metabolomics analysis, using a simplified and much less expensive silylation process with trimethylsilyl cyanide (TMSCN), was conducted to investigate metabolic abnormalities in stomach cancer cells. Under optimized conditions for derivatization by TMSCN and methanol extraction, 228 metabolites were detected using GC/MS spectrometry analysis, and 89 metabolites were identified using standard compounds and the NIST database. Ten metabolite levels were found to be lower in stomach cancer cells relative to normal cells. Among those ten metabolites, four metabolites-ribose, proline, pyroglutamic acid, and glucose-were known to be linked to cancers. In particular, pyroglutamic acid level showed a drastic reduction of 22-fold in stomach cancer cells. Since glutamine and glutamic acid are known to undergo cyclization to pyroglutamic acid, the 22-fold reduction might be the actual reduction in the levels of glutamine and/or glutamic acid-both known to be cancer-related. Hence, the marked reduction in pyroglutamic acid level might serve as a biomarker to aid early detection of stomach cancer. Graphical abstract.

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.

Metabolomics for a Millenniums-Old Crop: Tea Plant ( Camellia sinensis)

Tea cultivation and utilization dates back to antiquity. Today it is the most widely consumed beverage on earth due to its pleasant taste and several beneficial health properties attributed to specific metabolites. Metabolomics has a tremendous potential to correlate tea metabolites with taste and health properties in humans. Our review on the current application of metabolomics in the science of tea suggests that metabolomics is a promising frontier in the evaluation of tea quality, identification of functional genes responsible for key metabolites, investigation of their metabolic regulation, and pathway analysis in the tea plant. Furthermore, the challenges, possible solutions, and the prospects of metabolomics in tea science are reviewed.

Comparative Analysis of Fruit Metabolites and Pungency Candidate Genes Expression between Bhut Jolokia and Other Capsicum Species

Bhut jolokia, commonly known as Ghost chili, a native Capsicum species found in North East India was recorded as the naturally occurring hottest chili in the world by the Guinness Book of World Records in 2006. Although few studies have reported variation in pungency content of this particular species, no study till date has reported detailed expression analysis of candidate genes involved in capsaicinoids (pungency) biosynthesis pathway and other fruit metabolites. Therefore, the present study was designed to evaluate the diversity of fruit morphology, fruiting habit, capsaicinoids and other metabolite contents in 136 different genotypes mainly collected from North East India. Significant intra and inter-specific variations for fruit morphological traits, fruiting habits and 65 fruit metabolites were observed in the collected Capsicum germplasm belonging to three Capsicum species i.e., Capsicum chinense (Bhut jolokia, 63 accessions), C. frutescens (17 accessions) and C. annuum (56 accessions). The pungency level, measured in Scoville Heat Unit (SHU) and antioxidant activity measured by 2, 2-diphenyl-1-picrylhydrazyl (DPPH) free radical scavenging assay showed maximum levels in C. chinense accessions followed by C. frutescens accessions, while C. annuum accessions showed the lowest value for both the traits. The number of different fruit metabolites detected did not vary significantly among the different species but the metabolite such as benzoic acid hydroxyl esters identified in large percentage in majority of C. annuum genotypes was totally absent in the C. chinense genotypes and sparingly present in few genotypes of C. frutescens. Significant correlations were observed between fruit metabolites capsaicin, dihydrocapsaicin, hexadecanoic acid, cyclopentane, α-tocopherol and antioxidant activity. Furthermore, comparative expression analysis (through qRT-PCR) of candidate genes involved in capsaicinoid biosynthesis pathway revealed many fold higher expression of majority of the genes in C. chinense compared to C. frutescens and C. annuum suggesting that the possible reason for extremely high pungency might be due to the higher level of candidate gene(s) expression although nucleotide variation in pungency related genes may also be involved in imparting variations in level of pungency.

PCI-GC-MS-MS approach for identification of non-amino organic acid and amino acid profiles

Alkyl chloroformate have been wildly used for the fast derivatization of metabolites with amino and/or carboxyl groups, coupling of powerful separation and detection systems, such as GC-MS, which allows the comprehensive analysis of non-amino organic acids and amino acids. The reagents involving n-alkyl chloroformate and n-alcohol are generally employed for providing symmetric labeling terminal alkyl chain with the same length. Here, we developed an asymmetric labeling strategy and positive chemical ionization gas chromatography-tandem mass spectrometry (PCI-GC-MS-MS) approach for determination of non-amino organic acids and amino acids, as well as the short chain fatty acids. Carboxylic and amino groups could be selectively labelled by propyl and ethyl groups, respectively. The specific neutral loss of C₃H₈O (60Da), C₃H₅O₂ (74Da) and C₄H₈O₂ (88Da) were useful in the selective identification for qualitative analysis of organic acids and amino acid derivatives. PCI-GC-MS-MS using multiple reaction monitoring (MRM) was applied for semi-quantification of typical non-amino organic acids and amino acids. This method exhibited a wide range of linear range, good regression coefficient (R²) and repeatability. The relative standard deviation (RSD) of targeted metabolites showed excellent intra- and inter-day precision (<5%). Our method provided a qualitative and semi-quantitative PCI-GC-MS-MS, coupled with alkyl chloroformate derivatization.

The double-edged sword of the mammalian oocyte--advantages, drawbacks and approaches for basic and clinical analysis at the single cell level

Oocytes are usually the largest cells in the body and as such offer unique opportunities for single-cell analysis. Unfortunately, these cells are also some of the rarest in the mammalian female, usually necessitating single-cell analysis. In cases of infertility in humans, determining the quality of the oocyte is often restricted to a morphological analysis or to the study of cellular behaviors in the developing embryo. Minimally invasive approaches could greatly assist the clinician to prioritize oocytes for fertilization or following fertilization, which embryo to transfer back into the woman. Transcriptomics of human and mouse oocytes may have great utility, and recently it was learned that the polar body faithfully reflects the transcript prevalence in the oocyte. The polar body may thus serve as a minimally invasive proxy for an oocyte in the clinic. In the mouse, the transcriptomes of oocytes from mice of the same strain are markedly similar; no significant differences are apparent in transcript prevalence or identity. In human oocytes however, the transcript pool is highly variable. This is likely the result of different histories of each oocyte, in the age of the donor woman, the different hormonal exposures and the prolonged time from specification of the primary oocyte to the fully grown and ovulated egg. This variability in human oocytes also emphasizes the need for cell-by-cell analysis of the oocytes in vitro; which oocytes have a better potential for fertilization and development? To this end, new imaging capabilities are being employed. For example, a single-cell analytical device for oocytes (the simple perfusion apparatus, or SPA) enables investigators to load multiple oocytes in individual wells, to visualize them on the microscope and to use controlled temperature and media flow by perfusion for optimal clinical applications. Recently, developed Raman microspectroscopy approaches suggest that this imaging modality may enable more in-depth analysis of the molecular characteristics of an oocyte that, in combination with the SPA and transcriptomic approaches, might assist the clinician to prioritize more effectively human oocytes and embryos for transfer into women. This review is intended to update the reader on the status of the examination of single oocytes from a variety of approaches and to emphasize areas that may be primed for advancement in the near future.

Subcellular metabolite and lipid analysis of Xenopus laevis eggs by LAESI mass spectrometry

Xenopus laevis eggs are used as a biological model system for studying fertilization and early embryonic development in vertebrates. Most methods used for their molecular analysis require elaborate sample preparation including separate protocols for the water soluble and lipid components. In this study, laser ablation electrospray ionization (LAESI), an ambient ionization technique, was used for direct mass spectrometric analysis of X. laevis eggs and early stage embryos up to five cleavage cycles. Single unfertilized and fertilized eggs, their animal and vegetal poles, and embryos through the 32-cell stage were analyzed. Fifty two small metabolite ions, including glutathione, GABA and amino acids, as well as numerous lipids including 14 fatty acids, 13 lysophosphatidylcholines, 36 phosphatidylcholines and 29 triacylglycerols were putatively identified. Additionally, some proteins, for example thymosin β4 (Xen), were also detected. On the subcellular level, the lipid profiles were found to differ between the animal and vegetal poles of the eggs. Radial profiling revealed profound compositional differences between the jelly coat vitelline/plasma membrane and egg cytoplasm. Changes in the metabolic profile of the egg following fertilization, e.g., the decline of polyamine content with the development of the embryo were observed using LAESI-MS. This approach enables the exploration of metabolic and lipid changes during the early stages of embryogenesis.

Challenges of analyzing different classes of metabolites by a single analytical method

Complex biological samples include thousands of metabolites that range widely in both physiochemical properties and concentration. Simultaneously analyzing metabolites with different properties using a single analytical method is very challenging. The analytical process for metabolites comprises multiple steps including sampling, quenching, sample preparation, separation and detection. Each step can have a significant effect on the reliability and precision of ultimate analytic results. The aim of review is a discussion of considerations and challenges for the simultaneous analysis of metabolites using LC– and GC–MS systems. The review discusses available methodology for each analytical step, and presents the limitations and advantages of each method for the large-scale targeted metabolomics analysis of human and animal biological samples.

Analysis of endogenous nucleotides by single cell capillary electrophoresis-mass spectrometry

Analytical technologies that enable investigations at the single cell level facilitate a range of studies; here a lab-fabricated capillary electrophoresis-electrospray ionization-mass spectrometry (CE-ESI-MS) platform was used to analyze anionic metabolites from individual Aplysia californica neurons. The system employs a customized coaxial sheath-flow nanospray interface connected to a separation capillary, with the sheath liquid and separation buffer optimized to ensure a stable spray. The method provided good repeatability of separation and reliable detection sensitivity for 16 mono-, di- and triphosphate nucleosides. For a range of anionic analytes, including cyclic adenosine monophosphate (cAMP), adenosine diphosphate (ADP) and adenosine triphosphate (ATP), the detection limits were in the low nanomolar range (<22 nM). A large Aplysia R2 neuron was used to demonstrate the ability of CE-ESI-MS to quantitatively characterize anionic metabolites within individual cells, with 15 nucleotides and derivatives detected. Following the method validation process, we probed smaller, 60 μm diameter Aplysia sensory neurons where sample stacking was used as a simple on-line analyte preconcentration approach. The calculated energy balance ([ATP] + 0.5 × [ADP])/([AMP] + [ADP] + [ATP]) of these cells was comparable with the value obtained from bulk samples.

Metabolic control of oocyte development: linking maternal nutrition and reproductive outcomes

Obesity, diabetes, and related metabolic disorders are major health issues worldwide. As the epidemic of metabolic disorders continues, the associated medical co-morbidities, including the detrimental impact on reproduction, increase as well. Emerging evidence suggests that the effects of maternal nutrition on reproductive outcomes are likely to be mediated, at least in part, by oocyte metabolism. Well-balanced and timed energy metabolism is critical for optimal development of oocytes. To date, much of our understanding of oocyte metabolism comes from the effects of extrinsic nutrients on oocyte maturation. In contrast, intrinsic regulation of oocyte development by metabolic enzymes, intracellular mediators, and transport systems is less characterized. Specifically, decreased acid transport proteins levels, increased glucose/lipid content and elevated reactive oxygen species in oocytes have been implicated in meiotic defects, organelle dysfunction and epigenetic alteration. Therefore, metabolic disturbances in oocytes may contribute to the diminished reproductive potential experienced by women with metabolic disorders. In-depth research is needed to further explore the underlying mechanisms. This review also discusses several approaches for metabolic analysis. Metabolomic profiling of oocytes, the surrounding granulosa cells, and follicular fluid will uncover the metabolic networks regulating oocyte development, potentially leading to the identification of oocyte quality markers and prevention of reproductive disease and poor outcomes in offspring.

Spatiotemporal lipid profiling during early embryo development of Xenopus laevis using dynamic ToF-SIMS imaging

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging has been used for the direct analysis of single intact Xenopus laevis embryo surfaces, locating multiple lipids during fertilization and the early embryo development stages with subcellular lateral resolution (∼4 μm). The method avoids the complicated sample preparation for lipid analysis of the embryos, which requires selective chemical extraction of a pool of samples and chromatographic separation, while preserving the spatial distribution of biological species. The results show ToF-SIMS is capable of profiling multiple components (e.g., glycerophosphocholine, SM, cholesterol, vitamin E, diacylglycerol, and triacylglycerol) in a single X. laevis embryo. We observe lipid remodeling during fertilization and early embryo development via time course sampling. The study also reveals the lipid distribution on the gamete fusion site. The methodology used in the study opens the possibility of studying developmental biology using high resolution imaging MS and of understanding the functional role of the biological molecules.

Determination of metabolic organic acids in cerebrospinal fluid by microchip electrophoresis

A new MCE method for the determination of oxalic, citric, glycolic, lactic, and 2- and 3-hydroxybutyric acids, indicators of some metabolic and neurological diseases, in cerebrospinal fluid (CSF) was developed. MCE separations were performed on a PMMA microchip with coupled channels at lower pH (5.5) to prevent proteins interference. A double charged counter-ion, BIS-TRIS propane, was very effective in resolving the studied organic acids. The limits of detection (S/N = 3) ranging from 0.1 to 1.6 μM were obtained with the aid of contact conductivity detector implemented directly on the microchip. RSDs for migration time and peak area of organic acids in artificial and CSF samples were <0.8 and <9.7%, respectively. Recoveries of organic acids in untreated CSF samples on the microchip varied from 91 to 104%. Elimination of chloride interference, a major anionic constituent of CSF, has been reached by two approaches: (i) the use of coupled channels microchip in a column switching mode when approximately 97-99% of chloride was removed electrophoretically in the first separation channel and (ii) the implementation of micro-SPE with silver-form resin prior to the MCE analysis, which selectively removed chloride from undeproteinized CSF samples.

Looking back into the future: 30 years of metabolomics at TNO

Metabolites have played an essential role in our understanding of life, health, and disease for thousands of years. This domain became much more important after the concept of metabolism was discovered. In the 1950s, mass spectrometry was coupled to chromatography and made the technique more application-oriented and allowed the development of new profiling technologies. Since 1980, TNO has performed system-based metabolic profiling of body fluids, and combined with pattern recognition has led to many discoveries and contributed to the field known as metabolomics and systems biology. This review describes the development of related concepts and applications at TNO in the biomedical, pharmaceutical, nutritional, and microbiological fields, and provides an outlook for the future.

In Situ Pressure Probe Sampling and UV-MALDI MS for Profiling Metabolites in Living Single Cells

In this work we describe the use of a combination of a cell pressure probe and a UV-matrix-assisted laser desorption/ionization time of flight (UV-MALDI-TOF) mass spectrometer for the in situ picoliter sampling and shotgun metabolite profiling of living single cells of plants. In addition to quantifiable sampling, the pressure probe has some unique features which differentiate it from other single-cell analytical tools. Cell wall and plasma membrane properties and water relations of in situ living single cells can be analyzed before sampling the cell sap. In addition, the fully-controlled sampling of cells located at different depths in plant tissues, measurement of the sample volume, and the addition of internal standards are facilitated by the pressure probe. Using a variety of organic compounds and nanoparticles as UV-MALDI matrices, metabolites from neutral carbohydrates to amino acids and other metabolites can be detected through UV-MALDI-TOF mass spectrometry analyses of picoliter-sized, single-cell samples.

Intracellular metabolite profiling of platelets: evaluation of extraction processes and chromatographic strategies

An extraction method for intracellular metabolite profiling should ideally be able to recover the broadest possible range of metabolites present in a sample. However, the development of such methods is hampered by the diversity of the physico-chemical properties of metabolites as well as by the specific characteristics of samples and cells. In this study, we report the optimization of an UPLC-MS method for the metabolite analysis of platelet samples. The optimal analytical protocol was determined by testing seven different extraction methods as well as by employing two different LC-MS methods, in which the metabolites were separated by using hydrophilic interaction liquid chromatography (HILIC) and reversed phase liquid chromatography (RPLC). The optimal conditions were selected using the coverage of the platelets' metabolome, the response of the identified metabolites, the reproducibility of the analytical method, and the time of the analysis as main evaluation criteria. Our results show that methanol-water (7:3) extraction coupled with HILIC-MS method provides the best compromise, allowing identification of 107 metabolites in a platelet cell extract sample, 91% of them with a RSD% lower than 20. A higher number of metabolites could be detected when analyzing the platelet samples with two different LC-MS methods or when using complementary extraction methods in parallel.

Monitoring metabolites consumption and secretion in cultured cells using ultra-performance liquid chromatography quadrupole-time of flight mass spectrometry (UPLC-Q-ToF-MS)

Here we present an ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) method for extracellular measurements of known and unexpected metabolites in parallel. The method was developed by testing 86 metabolites, including amino acids, organic acids, sugars, purines, pyrimidines, vitamins, and nucleosides, that can be resolved by combining chromatographic and m/z dimensions. Subsequently, a targeted quantitative method was developed for 80 metabolites. The presented method combines a UPLC approach using hydrophilic interaction liquid chromatography (HILIC) and MS detection achieved by a hybrid quadrupole-time of flight (Q-ToF) mass spectrometer. The optimal setup was achieved by evaluating reproducibility and repeatability of the analytical platforms using pooled quality control samples to minimize the drift in instrumental performance over time. Then, the method was validated by analyzing extracellular metabolites from acute lymphoblastic leukemia cell lines (MOLT-4 and CCRF-CEM) treated with direct (A-769662) and indirect (AICAR) AMP activated kinase (AMPK) activators, monitoring uptake and secretion of the targeted compound over time. This analysis pointed towards a perturbed purine and pyrimidine catabolism upon AICAR treatment. Our data suggest that the method presented can be used for qualitative and quantitative analysis of extracellular metabolites and it is suitable for routine applications such as in vitro drug screening.

Quantitative metabolomics based on gas chromatography mass spectrometry: status and perspectives

Metabolomics involves the unbiased quantitative and qualitative analysis of the complete set of metabolites present in cells, body fluids and tissues (the metabolome). By analyzing differences between metabolomes using biostatistics (multivariate data analysis; pattern recognition), metabolites relevant to a specific phenotypic characteristic can be identified. However, the reliability of the analytical data is a prerequisite for correct biological interpretation in metabolomics analysis. In this review the challenges in quantitative metabolomics analysis with regards to analytical as well as data preprocessing steps are discussed. Recommendations are given on how to optimize and validate comprehensive silylation-based methods from sample extraction and derivatization up to data preprocessing and how to perform quality control during metabolomics studies. The current state of method validation and data preprocessing methods used in published literature are discussed and a perspective on the future research necessary to obtain accurate quantitative data from comprehensive GC-MS data is provided.

Mass spectrometry strategies in metabolomics

MS has evolved as a critical component in metabolomics, which seeks to answer biological questions through large-scale qualitative and quantitative analyses of the metabolome. MS-based metabolomics techniques offer an excellent combination of sensitivity and selectivity, and they have become an indispensable platform in biology and metabolomics. In this minireview, various MS technologies used in metabolomics are briefly discussed, and future needs are suggested.

Low-parachor solvents extraction and thermostated micro-thin-layer chromatography separation for fast screening and classification of spirulina from pharmaceutical formulations and food samples

The goal of this paper is to demonstrate the separation and detection capability of eco-friendly micro-TLC technique for the classification of spirulina and selected herbs from pharmaceutical and food products. Target compounds were extracted using relatively low-parachor liquids. A number of the spirulina samples which originated from pharmaceutical formulations and food products, were isolated using a simple one step extraction with small volume of methanol, acetone or tetrahydrofuran. Herb samples rich in chlorophyll dyes were analyzed as reference materials. Quantitative data derived from micro-plates under visible light conditions and after iodine staining were explored using chemometrics tools including cluster analysis and principal components analysis. Using this method we could easily distinguish genuine spirulina and non-spirulina samples as well as fresh from expired commercial products and furthermore, we could identify some biodegradation peaks appearing on micro-TLC profiles. This methodology can be applied as a fast screening or fingerprinting tool for the classification of genuine spirulina and herb samples and in particular may be used commercially for the rapid quality control screening of products. Furthermore, this approach allows low-cost fractionation of target substances including cyanobacteria pigments in raw biological or environmental samples for preliminary chemotaxonomic investigations. Due to the low consumption of the mobile phase (usually less than 1 mL per run), this method can be considered as environmentally friendly analytical tool, which may be an alternative for fingerprinting protocols based on HPLC machines and simple separation systems involving planar micro-fluidic or micro-chip devices.

Capillary separations in metabolomics

Capillary-based separations offer increased resolution, low mass LOD and, in the case of MS, higher sensitivity. The chemical diversity and wide dynamic range of the metabolome requires systems that offer breadth and depth of analysis. In this review, we will highlight novel chemical innovations, technological advancements and various applications of capillary separations in the field of metabolomics.

Qualitative metabolome analysis of human cerebrospinal fluid by 13C-/12C-isotope dansylation labeling combined with liquid chromatography Fourier transform ion cyclotron resonance mass spectrometry

Metabolome analysis of human cerebrospinal fluid (CSF) is challenging because of low abundance of metabolites present in a small volume of sample. We describe and apply a sensitive isotope labeling LC-MS technique for qualitative analysis of the CSF metabolome. After a CSF sample is divided into two aliquots, they are labeled by (13)C-dansyl and (12)C-dansyl chloride, respectively. The differentially labeled aliquots are then mixed and subjected to LC-MS using Fourier-transform ion cyclotron resonance mass spectrometry (FTICR MS). Dansylation offers significant improvement in the performance of chromatography separation and detection sensitivity. Moreover, peaks detected in the mass spectra can be readily analyzed for ion pair recognition and database search based on accurate mass and/or retention time information. It is shown that about 14,000 features can be detected in a 25-min LC-FTICR MS run of a dansyl-labeled CSF sample, from which about 500 metabolites can be profiled. Results from four CSF samples are compared to gauge the detectability of metabolites by this method. About 261 metabolites are commonly detected in replicate runs of four samples. In total, 1132 unique metabolite ion pairs are detected and 347 pairs (31%) matched with at least one metabolite in the Human Metabolome Database. We also report a dansylation library of 220 standard compounds and, using this library, about 85 metabolites can be positively identified. Among them, 21 metabolites have never been reported to be associated with CSF. These results illustrate that the dansylation LC-FTICR MS method can be used to analyze the CSF metabolome in a more comprehensive manner.

Evaluation of automated sample preparation, retention time locked gas chromatography-mass spectrometry and data analysis methods for the metabolomic study of Arabidopsis species

In this paper, automated sample preparation, retention time locked gas chromatography-mass spectrometry (GC-MS) and data analysis methods for the metabolomics study were evaluated. A miniaturized and automated derivatisation method using sequential oximation and silylation was applied to a polar extract of 4 types (2 types×2 ages) of Arabidopsis thaliana, a popular model organism often used in plant sciences and genetics. Automation of the derivatisation process offers excellent repeatability, and the time between sample preparation and analysis was short and constant, reducing artifact formation. Retention time locked (RTL) gas chromatography-mass spectrometry was used, resulting in reproducible retention times and GC-MS profiles. Two approaches were used for data analysis. XCMS followed by principal component analysis (approach 1) and AMDIS deconvolution combined with a commercially available program (Mass Profiler Professional) followed by principal component analysis (approach 2) were compared. Several features that were up- or down-regulated in the different types were detected.

Advances in mass spectrometry applied to pharmaceutical metabolomics

Metabolomics, also referred to in the literature as metabonomics, is a relatively new systems biology tool for drug discovery and development and is increasingly being used to obtain a detailed picture of a drug's effect on the body. Metabolomics is the qualitative assessment and relative or absolute quantitative measurement of the endogenous metabolome, defined as the complement of all native small molecules (metabolites less than 1,500 Da). A metabolomics study frequently involves the comparative analysis of sample sets from a normal state and a perturbed state, where the perturbation can be of any nature, such as genetic knockout, administration of a drug, or change in diet or lifestyle. Advances in mass spectrometry (MS) technologies including direct introduction or in-line chromatographic separation modes, ionization techniques, mass analyzers, and detection methods have provided powerful tools to assess the molecular changes in the metabolome. This review focuses on advances in MS pertaining to the analytical data generation for the main metabolomics methods, namely, fingerprinting, nontargeted, and targeted approaches, as they are applied to pharmaceutical drug discovery and development.

13C metabolic flux analysis in complex systems

Experimental determination of in vivo metabolic rates by methods of (13)C metabolic flux analysis is a pivotal approach to unravel structure and regulation of metabolic networks, in particular with microorganisms grown in minimal media. However, the study of real-life and eukaryotic systems calls for the quantification of fluxes also in cellular compartments, rich media, cell-wide metabolic networks, dynamic systems or single cells. These scenarios drastically increase the complexity of the task, which is only partly dealt by existing approaches that rely on rigorous simulations of label propagation through metabolic networks and require multiple labeling experiments or a priori information on pathway inactivity to simplify the problem. Albeit qualitative and largely driven by human interpretation, statistical analysis of measured (13)C-patterns remains the exclusive alternative to comprehensively handle such complex systems. In the future, this practice will be complemented by novel modeling frameworks to assay particular fluxes within a network by stable isotopic tracer for targeted validation of well-defined hypotheses.