Toward Global Metabolomics Analysis with Hydrophilic Interaction Liquid Chromatography–Mass Spectrometry: Improved Metabolite Identification by Retention Time Prediction

Discriminating precursors of common fragments for large-scale metabolite profiling by triple quadrupole mass spectrometry

MOTIVATION

The goal of large-scale metabolite profiling is to compare the relative concentrations of as many metabolites extracted from biological samples as possible. This is typically accomplished by measuring the abundances of thousands of ions with high-resolution and high mass accuracy mass spectrometers. Although the data from these instruments provide a comprehensive fingerprint of each sample, identifying the structures of the thousands of detected ions is still challenging and time intensive. An alternative, less-comprehensive approach is to use triple quadrupole (QqQ) mass spectrometry to analyze predetermined sets of metabolites (typically fewer than several hundred). This is done using authentic standards to develop QqQ experiments that specifically detect only the targeted metabolites, with the advantage that the need for ion identification after profiling is eliminated.

RESULTS

Here, we propose a framework to extend the application of QqQ mass spectrometers to large-scale metabolite profiling. We aim to provide a foundation for designing QqQ multiple reaction monitoring (MRM) experiments for each of the 82 696 metabolites in the METLIN metabolite database. First, we identify common fragmentation products from the experimental fragmentation data in METLIN. Then, we model the likelihoods of each precursor structure in METLIN producing each common fragmentation product. With these likelihood estimates, we select ensembles of common fragmentation products that minimize our uncertainty about metabolite identities. We demonstrate encouraging performance and, based on our results, we suggest how our method can be integrated with future work to develop large-scale MRM experiments.

AVAILABILITY AND IMPLEMENTATION

Our predictions, Supplementary results, and the code for estimating likelihoods and selecting ensembles of fragmentation reactions are made available on the lab website at http://pattilab.wustl.edu/FragPred.

Incorporating peak grouping information for alignment of multiple liquid chromatography-mass spectrometry datasets

Motivation: The combination of liquid chromatography and mass spectrometry (LC/MS) has been widely used for large-scale comparative studies in systems biology, including proteomics, glycomics and metabolomics. In almost all experimental design, it is necessary to compare chromatograms across biological or technical replicates and across sample groups. Central to this is the peak alignment step, which is one of the most important but challenging preprocessing steps. Existing alignment tools do not take into account the structural dependencies between related peaks that coelute and are derived from the same metabolite or peptide. We propose a direct matching peak alignment method for LC/MS data that incorporates related peaks information (within each LC/MS run) and investigate its effect on alignment performance (across runs). The groupings of related peaks necessary for our method can be obtained from any peak clustering method and are built into a pair-wise peak similarity score function. The similarity score matrix produced is used by an approximation algorithm for the weighted matching problem to produce the actual alignment result.

Results: We demonstrate that related peak information can improve alignment performance. The performance is evaluated on a set of benchmark datasets, where our method performs competitively compared to other popular alignment tools.

Availability: The proposed alignment method has been implemented as a stand-alone application in Python, available for download at http://github.com/joewandy/peak-grouping-alignment.

Contact:Simon.Rogers@glasgow.ac.uk

Supplementary information:Supplementary data are available at Bioinformatics online.

LC-MS-based absolute metabolite quantification: application to metabolic flux measurement in trypanosomes

Human African trypanosomiasis is a neglected tropical disease caused by the protozoan parasite, Trypanosoma brucei. In the mammalian bloodstream, the trypanosome's metabolism differs significantly from that of its host. For example, the parasite relies exclusively on glycolysis for energy source. Recently, computational and mathematical models of trypanosome metabolism have been generated to assist in understanding the parasite metabolism with the aim of facilitating drug development. Optimisation of these models requires quantitative information, including metabolite concentrations and/or metabolic fluxes that have been hitherto unavailable on a large scale. Here, we have implemented an LC-MS-based method that allows large scale quantification of metabolite levels by using U-¹³C-labelled E.coli extracts as internal standards. Known amounts of labelled E. coli extract were added into the parasite samples, as well as calibration standards, and used to obtain calibration curves enabling us to convert intensities into concentrations. This method allowed us to reliably quantify the changes of 43 intracellular metabolites and 32 extracellular metabolites in the medium over time. Based on the absolute quantification, we were able to compute consumption and production fluxes. These quantitative data can now be used to optimise computational models of parasite metabolism.

Potent trypanocidal curcumin analogs bearing a monoenone linker motif act on trypanosoma brucei by forming an adduct with trypanothione

We have previously reported that curcumin analogs with a C7 linker bearing a C4-C5 olefinic linker with a single keto group at C3 (enone linker) display midnanomolar activity against the bloodstream form of Trypanosoma brucei. However, no clear indication of their mechanism of action or superior antiparasitic activity relative to analogs with the original di-ketone curcumin linker was apparent. To further investigate their utility as antiparasitic agents, we compare the cellular effects of curcumin and the enone linker lead compound 1,7-bis(4-hydroxy-3-methoxyphenyl)hept-4-en-3-one (AS-HK014) here. An AS-HK014-resitant line, trypanosomes adapted to AS-HK014 (TA014), was developed by in vitro exposure to the drug. Metabolomic analysis revealed that exposure to AS-HK014, but not curcumin, rapidly depleted glutathione and trypanothione in the wild-type line, although almost all other metabolites were unchanged relative to control. In TA014 cells, thiol levels were similar to untreated wild-type cells and not significantly depleted by AS-HK014. Adducts of AS-HK014 with both glutathione and trypanothione were identified in AS-HK014-exposed wild-type cells and reproduced by chemical reaction. However, adduct accumulation in sensitive cells was much lower than in resistant cells. TA014 cells did not exhibit any changes in sequence or protein levels of glutathione synthetase and γ-glutamylcysteine synthetase relative to wild-type cells. We conclude that monoenone curcuminoids have a different mode of action than curcumin, rapidly and specifically depleting thiol levels in trypanosomes by forming an adduct. This adduct may ultimately be responsible for the highly potent trypanocidal and antiparasitic activity of the monoenone curcuminoids.

MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments

Due to their sensitivity and speed, mass-spectrometry based analytical technologies are widely used to in metabolomics to characterize biological phenomena. To address issues like metadata organization, quality assessment, data processing, data storage, and, finally, submission to public repositories, bioinformatic pipelines of a non-interactive nature are often employed, complementing the interactive software used for initial inspection and visualization of the data. These pipelines often are created as open-source software allowing the complete and exhaustive documentation of each step, ensuring the reproducibility of the analysis of extensive and often expensive experiments. In this paper, we will review the major steps which constitute such a data processing pipeline, discussing them in the context of an open-source software for untargeted MS-based metabolomics experiments recently developed at our institute. The software has been developed by integrating our metaMS R package with a user-friendly web-based application written in Grails. MetaMS takes care of data pre-processing and annotation, while the interface deals with the creation of the sample lists, the organization of the data storage, and the generation of survey plots for quality assessment. Experimental and biological metadata are stored in the ISA-Tab format making the proposed pipeline fully integrated with the Metabolights framework.

Retention time prediction for dereplication of natural products (CxHyOz) in LC-MS metabolite profiling

The detection and early identification of natural products (NPs) for dereplication purposes require efficient, high-resolution methods for the profiling of crude natural extracts. This task is difficult because of the high number of NPs in these complex biological matrices and because of their very high chemical diversity. Metabolite profiling using ultra-high pressure liquid chromatography coupled to high-resolution mass spectrometry (UHPLC–HR-MS) is very efficient for the separation of complex mixtures and provides molecular formula information as a first step in dereplication. This structural information alone or even combined with chemotaxonomic information is often not sufficient for unambiguous metabolite identification. In this study, a representative set of 260 NPs containing C, H, and O atoms only was analysed in generic UHPLC–HR-MS profiling conditions. Two easy to use quantitative structure retention relationship (QSRR) models were built based on the measured retention time and on eight simple physicochemical parameters calculated from the structures. First, an original approach using several partial least square (PLS) regressions according to the phytochemical classes provided satisfactory results with an easy calculation. Secondly, a unique artificial neural network (ANN) model provided similar results on the whole set of NPs but required dedicated software. The retention prediction methods described in this study were found to improve the level of confidence of the identification of given analytes among putative isomeric structures. Its applicability was verified for the dereplication of NPs in model plant extracts.

Separation of nucleobases, nucleosides, and nucleotides using two zwitterionic silica-based monolithic capillary columns coupled with tandem mass spectrometry

The capability of employing synthesized zwitterionic silica-based monolithic capillary columns (140 mm × 0.1mm) for separation of highly polar and hydrophilic nucleobases, nucleosides, and nucleotides in hydrophilic interaction chromatography is reported. The suitability of the columns for on-line conjunction with electrospray tandem mass spectrometry was explored. Our results show that the grafted layer of zwitterionic monomer ([2-(methacryloyloxy)ethyl]-dimethyl-(3-sulfopropyl)-ammonium hydroxide or 2-methacryloyloxyethyl phosphorylcholine) on the silica monolithic surface significantly improved the separation selectivity and reproducibility, as compared to the bare silica monolith. The stepwise elution from 90% to 70% of acetonitrile enabled separation of a complex sample mixture containing 21 compounds with a total analysis time less than 40 min.

High resolution mass spectrometry based techniques at the crossroads of metabolic pathways

The metabolome is the set of small molecular mass compounds found in biological media, and metabolomics, which refers to as the analysis of metabolome in a given biological condition, deals with the large scale detection and quantification of metabolites in biological media. It is a data driven and multidisciplinary approach combining analytical chemistry for data acquisition, and biostatistics, informatics and biochemistry for mining and interpretation of these data. Since the middle of the 2000s, high resolution mass spectrometry is widely used in metabolomics, mainly because the detection and identification of metabolites are improved compared to low resolution instruments. As the field of HRMS is quickly and permanently evolving, the aim of this work is to review its use in different aspects of metabolomics, including data acquisition, metabolite annotation, identification and quantification. At last, we would like to show that, thanks to their versatility, HRMS instruments are the most appropriate to achieve optimal metabolome coverage, at the border of other omics fields such as lipidomics and glycomics.

Nanotopographical induction of osteogenesis through adhesion, bone morphogenic protein cosignaling, and regulation of microRNAs

It is emerging that nanotopographical information can be used to induce osteogenesis from mesenchymal stromal cells from the bone marrow, and it is hoped that this nanoscale bioactivity can be utilized to engineer next generation implants. However, the osteogenic mechanism of surfaces is currently poorly understood. In this report, we investigate mechanism and implicate bone morphogenic protein (BMP) in up-regulation of RUNX2 and show that RUNX2 and its regulatory miRNAs are BMP sensitive. Our data demonstrate that osteogenic nanotopography promotes colocalization of integrins and BMP2 receptors in order to enhance osteogenic activity and that vitronectin is important in this interface. This provides insight that topographical regulation of adhesion can have effects on signaling cascades outside of cytoskeletal signaling and that adhesions can have roles in augmenting BMP signaling.

Stable isotope-labeling studies in metabolomics: new insights into structure and dynamics of metabolic networks

The rapid emergence of metabolomics has enabled system-wide measurements of metabolites in various organisms. However, advances in the mechanistic understanding of metabolic networks remain limited, as most metabolomics studies cannot routinely provide accurate metabolite identification, absolute quantification and flux measurement. Stable isotope labeling offers opportunities to overcome these limitations. Here we describe some current approaches to stable isotope-labeled metabolomics and provide examples of the significant impact that these studies have had on our understanding of cellular metabolism. Furthermore, we discuss recently developed software solutions for the analysis of stable isotope-labeled metabolomics data and propose the bioinformatics solutions that will pave the way for the broader application and optimal interpretation of system-scale labeling studies in metabolomics.

Metabolomic-based strategies for anti-parasite drug discovery

Metabolomics-based studies are proving of great utility in the analysis of modes of action (MOAs) and resistance mechanisms of drugs in parasitic protozoa. They have helped to determine the MOA of eflornithine, half of the gold standard combination therapy in use against human African trypanosomiasis (HAT), as well as the mechanism of resistance to this drug. In Leishmania, metabolomics has also given insight into the MOA of miltefosine, an alkylphospholipid. Several studies on antimony resistance in Leishmania have been conducted, analyzing the metabolic content of resistant lines, offering clues as to the MOA of this class of drugs. A study of chloroquine resistance in Plasmodium falciparum combined metabolomics techniques with other genetic and proteomic techniques to offer new insight into the role of the PfCRT protein. The MOA and mechanism of resistance to a group of halogenated pyrimidines in Trypanosoma brucei have also recently been elucidated. Effective as metabolomics techniques are, care must be taken in the design and implementation of these experiments, to ensure the resulting data are meaningful. This review outlines the steps required to conduct a metabolomics experiment as well as provide an overview of metabolomics-based drug research in protozoa to date.

Predicting retention time in hydrophilic interaction liquid chromatography mass spectrometry and its use for peak annotation in metabolomics

Liquid chromatography coupled to mass spectrometry (LCMS) is widely used in metabolomics due to its sensitivity, reproducibility, speed and versatility. Metabolites are detected as peaks which are characterised by mass-over-charge ratio (m/z) and retention time (rt), and one of the most critical but also the most challenging tasks in metabolomics is to annotate the large number of peaks detected in biological samples. Accurate m/z measurements enable the prediction of molecular formulae which provide clues to the chemical identity of peaks, but often a number of metabolites have identical molecular formulae. Chromatographic behaviour, reflecting the physicochemical properties of metabolites, should also provide structural information. However, the variation in rt between analytical runs, and the complicating factors underlying the observed time shifts, make the use of such information for peak annotation a non-trivial task. To this end, we conducted Quantitative Structure-Retention Relationship (QSRR) modelling between the calculated molecular descriptors (MDs) and the experimental retention times (rts) of 93 authentic compounds analysed using hydrophilic interaction liquid chromatography (HILIC) coupled to high resolution MS. A predictive QSRR model based on Random Forests algorithm outperformed a Multiple Linear Regression based model, and achieved a high correlation between predicted rts and experimental rts (Pearson's correlation coefficient = 0.97), with mean and median absolute error of 0.52 min and 0.34 min (corresponding to 5.1 and 3.2 % error), respectively. We demonstrate that rt prediction with the precision achieved enables the systematic utilisation of rts for annotating unknown peaks detected in a metabolomics study. The application of the QSRR model with the strategy we outlined enhanced the peak annotation process by reducing the number of false positives resulting from database queries by matching accurate mass alone, and enriching the reference library. The predicted rts were validated using either authentic compounds or ion fragmentation patterns.

BCKDH: the missing link in apicomplexan mitochondrial metabolism is required for full virulence of Toxoplasma gondii and Plasmodium berghei

While the apicomplexan parasites Plasmodium falciparum and Toxoplasma gondii are thought to primarily depend on glycolysis for ATP synthesis, recent studies have shown that they can fully catabolize glucose in a canonical TCA cycle. However, these parasites lack a mitochondrial isoform of pyruvate dehydrogenase and the identity of the enzyme that catalyses the conversion of pyruvate to acetyl-CoA remains enigmatic. Here we demonstrate that the mitochondrial branched chain ketoacid dehydrogenase (BCKDH) complex is the missing link, functionally replacing mitochondrial PDH in both T. gondii and P. berghei. Deletion of the E1a subunit of T. gondii and P. berghei BCKDH significantly impacted on intracellular growth and virulence of both parasites. Interestingly, disruption of the P. berghei E1a restricted parasite development to reticulocytes only and completely prevented maturation of oocysts during mosquito transmission. Overall this study highlights the importance of the molecular adaptation of BCKDH in this important class of pathogens.

The mitochondrial tricarboxylic acid (TCA) cycle is one of the core metabolic pathways of eukaryotic cells, which contributes to cellular energy generation and provision of essential intermediates for macromolecule synthesis. Apicomplexan parasites possess the complete sets of genes coding for the TCA cycle. However, they lack a key mitochondrial enzyme complex that is normally required for production of acetyl-CoA from pyruvate, allowing further oxidation of glycolytic intermediates in the TCA cycle. This study unequivocally resolves how acetyl-CoA is generated in the mitochondrion using a combination of genetic, biochemical and metabolomic approaches. Specifically, we show that T. gondii and P. bergei utilize a second mitochondrial dehydrogenase complex, BCKDH, that is normally involved in branched amino acid catabolism, to convert pyruvate to acetyl-CoA and further catabolize glucose in the TCA cycle. In T. gondii, loss of BCKDH leads to global defects in glucose metabolism, increased gluconeogenesis and a marked attenuation of growth in host cells and virulence in animals. In P. bergei, loss of BCKDH leads to a defect in parasite proliferation in mature red blood cells, although the mutant retains the capacity to proliferate within 'immature' reticulocytes, highlighting the role of host metabolism/physiology on the development of Plasmodium asexual stages.

The metabolic enzyme AdhE controls the virulence of Escherichia coli O157:H7

Classical studies have focused on the role that individual regulators play in controlling virulence gene expression. An emerging theme, however, is that bacterial metabolism also plays a key role in this process. Our previous work identified a series of proteins that were implicated in the regulation of virulence. One of these proteins was AdhE, a bi-functional acetaldehyde-CoA dehydrogenase and alcohol dehydrogenase. Deletion of its gene (adhE) resulted in elevated levels of extracellular acetate and a stark pleiotropic phenotype: strong suppression of the Type Three Secretion System (T3SS) and overexpression of non-functional flagella. Correspondingly, the adhE mutant bound poorly to host cells and was unable to swim. Furthermore, the mutant was significantly less virulent than its parent when tested in vivo, which supports the hypothesis that attachment and motility are central to the colonization process. The molecular basis by which AdhE affects virulence gene regulation was found to be multifactorial, involving acetate-stimulated transcription of flagella expression and post-transcriptional regulation of the T3SS through Hfq. Our study reveals fascinating insights into the links between bacterial physiology, the expression of virulence genes, and the underlying molecular mechanism mechanisms by which these processes are regulated.

MetAssign: probabilistic annotation of metabolites from LC-MS data using a Bayesian clustering approach

Motivation: The use of liquid chromatography coupled to mass spectrometry has enabled the high-throughput profiling of the metabolite composition of biological samples. However, the large amount of data obtained can be difficult to analyse and often requires computational processing to understand which metabolites are present in a sample. This article looks at the dual problem of annotating peaks in a sample with a metabolite, together with putatively annotating whether a metabolite is present in the sample. The starting point of the approach is a Bayesian clustering of peaks into groups, each corresponding to putative adducts and isotopes of a single metabolite.

Results: The Bayesian modelling introduced here combines information from the mass-to-charge ratio, retention time and intensity of each peak, together with a model of the inter-peak dependency structure, to increase the accuracy of peak annotation. The results inherently contain a quantitative estimate of confidence in the peak annotations and allow an accurate trade-off between precision and recall. Extensive validation experiments using authentic chemical standards show that this system is able to produce more accurate putative identifications than other state-of-the-art systems, while at the same time giving a probabilistic measure of confidence in the annotations.

Availability and implementation: The software has been implemented as part of the mzMatch metabolomics analysis pipeline, which is available for download at http://mzmatch.sourceforge.net/.

Contact:Ronan.Daly@glasgow.ac.uk

Supplementary information:Supplementary data are available at Bioinformatics online.

Mass spectrometry based identification of geometric isomers during metabolic stability study of a new cytotoxic sulfonamide derivatives supported by quantitative structure-retention relationships

A set of 15 new sulphonamide derivatives, presenting antitumor activity have been subjected to a metabolic stability study. The results showed that besides products of biotransformation, some additional peaks occurred in chromatograms. Tandem mass spectrometry revealed the same mass and fragmentation pathway, suggesting that geometric isomerization occurred. Thus, to support this hypothesis, quantitative structure-retention relationships were applied. Human liver microsomes were used as an in vitro model of metabolism. The biotransformation reactions were tracked by liquid chromatography assay and additionally, fragmentation mass spectra were recorded. In silico molecular modeling at a semi-empirical level was conducted as a starting point for molecular descriptor calculations. A quantitative structure-retention relationship model was built applying multiple linear regression based on selected three-dimensional descriptors. The studied compounds revealed high metabolic stability, with a tendency to form hydroxylated biotransformation products. However, significant chemical instability in conditions simulating human body fluids was noticed. According to literature and MS data geometrical isomerization was suggested. The developed in sillico model was able to describe the relationship between the geometry of isomer pairs and their chromatographic retention properties, thus it supported the hypothesis that the observed pairs of peaks are most likely geometric isomers. However, extensive structural investigations are needed to fully identify isomers' geometry. An effort to describe MS fragmentation pathways of novel chemical structures is often not enough to propose structures of potent metabolites and products of other chemical reactions that can be observed in compound solutions at early drug discovery studies. The results indicate that the relatively non-expensive and not time- and labor-consuming in sillico approach could be a good supportive tool assisting the identification of cis-trans isomers based on retention data. This methodology can be helpful during the structural identification of biotransformation and degradation products of new chemical entities--potential new drugs.

Benznidazole biotransformation and multiple targets in Trypanosoma cruzi revealed by metabolomics

BACKGROUND

The first line treatment for Chagas disease, a neglected tropical disease caused by the protozoan parasite Trypanosoma cruzi, involves administration of benznidazole (Bzn). Bzn is a 2-nitroimidazole pro-drug which requires nitroreduction to become active, although its mode of action is not fully understood. In the present work we used a non-targeted MS-based metabolomics approach to study the metabolic response of T. cruzi to Bzn.

METHODOLOGY/PRINCIPAL FINDINGS

Parasites treated with Bzn were minimally altered compared to untreated trypanosomes, although the redox active thiols trypanothione, homotrypanothione and cysteine were significantly diminished in abundance post-treatment. In addition, multiple Bzn-derived metabolites were detected after treatment. These metabolites included reduction products, fragments and covalent adducts of reduced Bzn linked to each of the major low molecular weight thiols: trypanothione, glutathione, γ-glutamylcysteine, glutathionylspermidine, cysteine and ovothiol A. Bzn products known to be generated in vitro by the unusual trypanosomal nitroreductase, TcNTRI, were found within the parasites, but low molecular weight adducts of glyoxal, a proposed toxic end-product of NTRI Bzn metabolism, were not detected.

CONCLUSIONS/SIGNIFICANCE

Our data is indicative of a major role of the thiol binding capacity of Bzn reduction products in the mechanism of Bzn toxicity against T. cruzi.

Multi-analytical platform metabolomic approach to study miltefosine mechanism of action and resistance in Leishmania

Miltefosine (MT) (hexadecylphosphocholine) was implemented to cope with resistance against antimonials, the classical treatment in Leishmaniasis. Given the scarcity of anti- Leishmania (L) drugs and the increasing appearance of resistance, there is an obvious need for understanding the mechanism of action and development of such resistance. Metabolomics is an increasingly popular tool in the life sciences due to it being a relatively fast and accurate technique that can be applied either with a particular focus or in a global manner to reveal new knowledge about biological systems. Three analytical platforms, gas chromatography (GC), liquid chromatography (LC) and capillary electrophoresis (CE) have been coupled to mass spectrometry (MS) to obtain a broad picture of metabolic changes in the parasite. Impairment of the polyamine metabolism from arginine (Arg) to trypanothione in susceptible parasites treated with MT was in some way expected, considering the reactive oxygen species (ROS) production described for MT. Importantly, in resistant parasites an increase in the levels of amino acids was the most outstanding feature, probably related to the adaptation of the resistant strain for its survival inside the parasitophorous vacuole.

Metabolite induction via microorganism co-culture: a potential way to enhance chemical diversity for drug discovery

Microorganisms have a long track record as important sources of novel bioactive natural products, particularly in the field of drug discovery. While microbes have been shown to biosynthesize a wide array of molecules, recent advances in genome sequencing have revealed that such organisms have the potential to yield even more structurally diverse secondary metabolites. Thus, many microbial gene clusters may be silent under standard laboratory growth conditions. In the last ten years, several methods have been developed to aid in the activation of these cryptic biosynthetic pathways. In addition to the techniques that demand prior knowledge of the genome sequences of the studied microorganisms, several genome sequence-independent tools have been developed. One of these approaches is microorganism co-culture, involving the cultivation of two or more microorganisms in the same confined environment. Microorganism co-culture is inspired by the natural microbe communities that are omnipresent in nature. Within these communities, microbes interact through signaling or defense molecules. Such compounds, produced dynamically, are of potential interest as new leads for drug discovery. Microorganism co-culture can be achieved in either solid or liquid media and has recently been used increasingly extensively to study natural interactions and discover new bioactive metabolites. Because of the complexity of microbial extracts, advanced analytical methods (e.g., mass spectrometry methods and metabolomics) are key for the successful detection and identification of co-culture-induced metabolites. This review focuses on co-culture studies that aim to increase the diversity of metabolites obtained from microbes. The various strategies are summarized with a special emphasis on the multiple methods of performing co-culture experiments. The analytical approaches for studying these interaction phenomena are discussed, and the chemical diversity and biological activity observed among the induced metabolites are described.

LC-MS-based holistic metabolic profiling. Problems, limitations, advantages, and future perspectives

The present review aims to critically discuss some of the major problems and limitations of LC-MS based metabolomics as experienced from an analytical chemistry standpoint. Metabolomics offers distinct advantages to a variety of life sciences. Continuous development of the field has been realised due to intensive efforts from a great many scientists from widely divergent backgrounds and research interests as demonstrated by the contents of this special issue. The aim of this commentary is to describe current hindrances to field's progress, (some unique to metabolomics, some common with other omics fields or with conventional targeted bioanalysis) to propose some potential solutions to overcome these constraints and to provide a future perspective for likely developments in the field.

Metabonomics study on nephrotoxicity induced by intraperitoneal and intravenous cisplatin administration using rapid resolution liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (RRLC-Q-TOF-MS)

Metabonomics was used to find characteristics of nephrotoxicity induced by IP or IV injection of cisplatin.

Isotopic ratio outlier analysis global metabolomics of Caenorhabditis elegans

We demonstrate the global metabolic analysis of Caenorhabditis elegans stress responses using a mass-spectrometry-based technique called isotopic ratio outlier analysis (IROA). In an IROA protocol, control and experimental samples are isotopically labeled with 95 and 5% (13)C, and the two sample populations are mixed together for uniform extraction, sample preparation, and LC-MS analysis. This labeling strategy provides several advantages over conventional approaches: (1) compounds arising from biosynthesis are easily distinguished from artifacts, (2) errors from sample extraction and preparation are minimized because the control and experiment are combined into a single sample, (3) measurement of both the molecular weight and the exact number of carbon atoms in each molecule provides extremely accurate molecular formulas, and (4) relative concentrations of all metabolites are easily determined. A heat-shock perturbation was conducted on C. elegans to demonstrate this approach. We identified many compounds that significantly changed upon heat shock, including several from the purine metabolism pathway. The metabolomic response information by IROA may be interpreted in the context of a wealth of genetic and proteomic information available for C. elegans . Furthermore, the IROA protocol can be applied to any organism that can be isotopically labeled, making it a powerful new tool in a global metabolomics pipeline.

Mapping an atlas of tissue-specific Drosophila melanogaster metabolomes by high resolution mass spectrometry

Metabolomics can provide exciting insights into organismal function, but most work on simple models has focussed on the whole organism metabolome, so missing the contributions of individual tissues. Comprehensive metabolite profiles for ten tissues from adult Drosophila melanogaster were obtained here by two chromatographic methods, a hydrophilic interaction (HILIC) method for polar metabolites and a lipid profiling method also based on HILIC, in combination with an Orbitrap Exactive instrument. Two hundred and forty two polar metabolites were putatively identified in the various tissues, and 251 lipids were observed in positive ion mode and 61 in negative ion mode. Although many metabolites were detected in all tissues, every tissue showed characteristically abundant metabolites which could be rationalised against specific tissue functions. For example, the cuticle contained high levels of glutathione, reflecting a role in oxidative defence; the alimentary canal (like vertebrate gut) had high levels of acylcarnitines for fatty acid metabolism, and the head contained high levels of ether lipids. The male accessory gland uniquely contained decarboxylated S-adenosylmethionine. These data thus both provide valuable insights into tissue function, and a reference baseline, compatible with the FlyAtlas.org transcriptomic resource, for further metabolomic analysis of this important model organism, for example in the modelling of human inborn errors of metabolism, aging or metabolic imbalances such as diabetes.

Mitochondrial substrate availability and its role in lipid-induced insulin resistance and proinflammatory signaling in skeletal muscle

The relationship between glucose and lipid metabolism has been of significant interest in understanding the pathogenesis of obesity-induced insulin resistance. To gain insight into this metabolic paradigm, we explored the potential interplay between cellular glucose flux and lipid-induced metabolic dysfunction within skeletal muscle. Here, we show that palmitate (PA)-induced insulin resistance and proinflammation in muscle cells, which is associated with reduced mitochondrial integrity and oxidative capacity, can be attenuated under conditions of glucose withdrawal or glycolytic inhibition using 2-deoxyglucose (2DG). Importantly, these glucopenic-driven improvements coincide with the preservation of mitochondrial function and are dependent on PA oxidation, which becomes markedly enhanced in the absence of glucose. Intriguingly, despite its ability to upregulate mitochondrial PA oxidation, glucose withdrawal did not attenuate PA-induced increases in total intramyocellular diacylglycerol and ceramide. Furthermore, consistent with our findings in cultured muscle cells, we also report enhanced insulin sensitivity and reduced proinflammatory tone in soleus muscle from obese Zucker rats fed a 2DG-supplemented diet. Notably, this improved metabolic status after 2DG dietary intervention is associated with markedly reduced plasma free fatty acids. Collectively, our data highlight the key role that mitochondrial substrate availability plays in lipid-induced metabolic dysregulation both in vitro and in vivo.

Metabolic adaptations of Leishmania donovani in relation to differentiation, drug resistance, and drug pressure

Antimonial (sodium stibogluconate, SSG) resistance and differentiation have been shown to be closely linked in Leishmania donovani, with SSG-resistant strains showing an increased capacity to generate infectious (metacyclic) forms. This is the first untargeted LC-MS metabolomics study which integrated both phenomena in one experimental design and provided insights into metabolic differences between three clinical L. donovani strains with a similar genetic background but different SSG-susceptibilities. We performed this analysis at different stages during promastigote growth and in the absence or presence of drug pressure. When comparing SSG-resistant and SSG-sensitive strains, a number of metabolic changes appeared to be constitutively present in all growth stages, pointing towards a clear link with SSG-resistance, whereas most metabolic changes were only detected in the stationary stage. These changes reflect the close intertwinement between SSG-resistance and an increased metacyclogenesis in resistant parasites. The metabolic changes suggest that SSG-resistant parasites have (i) an increased capacity for protection against oxidative stress; (ii) a higher fluidity of the plasma membrane; and (iii) a metabolic survival kit to better endure infection. These changes were even more pronounced in a resistant strain kept under Sb(III) drug pressure.

Quantitative structure-retention relationships models for prediction of high performance liquid chromatography retention time of small molecules: endogenous metabolites and banned compounds

Quantitative structure-retention relationship (QSRR) is a technique capable of improving the identification of analytes by predicting their retention time on a liquid chromatography column (LC) and/or their properties. This approach is particularly useful when LC is coupled with a high-resolution mass spectrometry (HRMS) platform. The main aim of the present study was to develop and describe appropriate QSRR models that provide usable predictive capability, allowing false positive identification to be removed during the interpretation of metabolomics data, while additionally increasing confidence of experimental results in doping control area. For this purpose, a dataset consisting of 146 drugs, metabolites and banned compounds from World Anti-Doping Agency (WADA) lists, was used. A QSRR study was carried out separately on high quality retention data determined by reversed-phase (RP-LC-HRMS) and hydrophilic interaction chromatography (HILIC-LC-HRMS) systems, employing a single protocol for each system. Multiple linear regression (MLR) was applied to construct the linear QSRR models based on a variety of theoretical molecular descriptors. The regression equations included a set of three descriptors for each model: ALogP, BELe6, R2p and ALogP(2), FDI, BLTA96, were used in the analysis of reversed-phase and HILIC column models, respectively. Statistically significant QSRR models (squared correlation coefficient for model fitting, R(2)=0.95 for RP and R(2)=0.84 for HILIC) indicate a strong correlation between retention time and the molecular descriptors. An evaluation of the best correlation models, performed by validation of each model using three tests (leave-one-out, leave-many-out, external tests), demonstrated the reliability of the models. This paper provides a practical and effective method for analytical chemists working with LC/HRMS platforms to improve predictive confidence of studies that seek to identify small molecules.

Nonvolatile salt-free stabilizer for the quantification of polar imipenem and cilastatin in human plasma using hydrophilic interaction chromatography/quadrupole mass spectrometry with contamination sensitive off-axis electrospray

A hydrophilic interaction chromatography/mass spectrometry (HILIC-MS)-based assay for imipenem (IMP) and cilastatin (CIL) was recently reported. This orthogonal electrospray ion source-based (ORS) assay utilized nonvolatile salt (unremovable) to stabilize IMI in plasma. Unfortunately, this method was not applicable to conventional MS with off-axis spray (OAS-MS) because MS sensitivity was rapidly deteriorated by the nonvolatile salt. Therefore, we aimed to find a nonvolatile salt- and ion suppression-free approach to stabilize and measure the analytes in plasma using OAS-MS. Acetonitrile and methanol were tested to stabilize the analytes in the plasma samples. The recoveries, matrix effects and stabilities of the analytes in the stabilizer-treated samples were studied. The variations in MS signal intensities were used as the indicator of the assay ruggedness. The results show that a mixture of methanol and acetonitrile (1:1) is best for the storage and measurement of IMP and CIL in human plasma. Utilization of this precipitant not only blocked the hydrolysis of the analytes in plasma but also resulted in an ion suppression-free, fast (120 s per sample) and sensitive detection. The sensitivity obtained using the less sensitive OAS-MS (API3000, 4 pg on column) is much greater than that of the published ORS-MS-based assay (API4000, 77 pg on column). The ruggedness of the assay was demonstrated by its constant MS signal intensity. In conclusion, an improved HILIC/MS-based assay for IMP and CIL was established. The approach presented here provides a simple solution to the challenge of analyzing hydrolytically unstable β-lactam antibiotics in biological samples.

Determination of antiprotozoal drug mechanisms by metabolomics approaches

The discovery, development and optimal utilization of pharmaceuticals can be greatly enhanced by knowledge of their modes of action. However, many drugs currently on the market act by unknown mechanisms. Untargeted metabolomics offers the potential to discover modes of action for drugs that perturb cellular metabolism. Development of high resolution LC-MS methods and improved data analysis software now allows rapid detection of drug-induced changes to cellular metabolism in an untargeted manner. Several studies have demonstrated the ability of untargeted metabolomics to provide unbiased target discovery for antimicrobial drugs, in particular for antiprotozoal agents. Furthermore, the utilization of targeted metabolomics techniques has enabled validation of existing hypotheses regarding antiprotozoal drug mechanisms. Metabolomics approaches are likely to assist with optimization of new drug candidates by identification of drug targets, and by allowing detailed characterization of modes of action and resistance of existing and novel antiprotozoal drugs.

Optimization of harvesting, extraction, and analytical protocols for UPLC-ESI-MS-based metabolomic analysis of adherent mammalian cancer cells

In this study, a liquid chromatography mass spectrometry (LC/MS)-based metabolomics protocol was optimized for quenching, harvesting, and extraction of metabolites from the human pancreatic cancer cell line Panc-1. Trypsin/ethylenediaminetetraacetic acid (EDTA) treatment and cell scraping in water were compared for sample harvesting. Four different extraction methods were compared to investigate the efficiency of intracellular metabolite extraction, including pure acetonitrile, methanol, methanol/chloroform/H2O, and methanol/chloroform/acetonitrile. The separation efficiencies of hydrophilic interaction chromatography (HILIC) and reversed-phase liquid chromatography (RPLC) with UPLC-QTOF-MS were also evaluated. Global metabolomics profiles were compared; the number of total detected features and the recovery and relative extraction efficiencies of target metabolites were assessed. Trypsin/EDTA treatment caused substantial metabolite leakage proving it inadequate for metabolomics studies. Direct scraping after flash quenching with liquid nitrogen was chosen to harvest Panc-1 cells which allowed for samples to be stored before extraction. Methanol/chloroform/H2O was chosen as the optimal extraction solvent to recover the highest number of intracellular features with the best reproducibility. HILIC had better resolution for intracellular metabolites of Panc-1 cells. This optimized method therefore provides high sensitivity and reproducibility for a variety of cellular metabolites and can be applicable to further LC/MS-based global metabolomics study on Panc-1 cell lines and possibly other cancer cell lines with similar chemical and physical properties.

Topographically targeted osteogenesis of mesenchymal stem cells stimulated by inclusion bodies attached to polycaprolactone surfaces

AIM

Bacterial inclusion bodies (IBs) are nanostructured (submicron), pseudospherical proteinaceous particles produced in recombinant bacteria resulting from ordered protein aggregation. Being mechanically stable, several physicochemical and biological properties of IBs can be tuned by appropriate selection of the producer strain and of culture conditions. It has been previously shown that IBs favor cell adhesion and surface colonization by mammalian cell lines upon decoration on materials surfaces, but how these biomaterials could influence the behavior of mesenchymal stem cells remains to be explored.

MATERIALS & METHODS

Here, the authors vary topography, stiffness and wettability using the IBs to decorate polycaprolactone surfaces on which mesenchymal stem cells are cultured.

RESULTS

The authors show that these topographies can be used to specifically target osteogenesis from mesenchymal stem cells, and through metabolomics, they show that the cells have increased energy demand during this bone-related differentiation.

CONCLUSION

IBs as topographies can be used not only to direct cell proliferation but also to target differentiation of mesenchymal stem cells.

Large-scale metabolome analysis and quantitative integration with genomics and proteomics data in Mycoplasma pneumoniae

Systems metabolomics, the identification and quantification of cellular metabolites and their integration with genomics and proteomics data, promises valuable functional insights into cellular biology. However, technical constraints, sample complexity issues and the lack of suitable complementary quantitative data sets prevented accomplishing such studies in the past. Here, we present an integrative metabolomics study of the genome-reduced bacterium Mycoplasma pneumoniae. We experimentally analysed its metabolome using a cross-platform approach. We explain intracellular metabolite homeostasis by quantitatively integrating our results with the cellular inventory of proteins, DNA and other macromolecules, as well as with available building blocks from the growth medium. We calculated in vivo catalytic parameters of glycolytic enzymes, making use of measured reaction velocities, as well as enzyme and metabolite pool sizes. A quantitative, inter-species comparison of absolute and relative metabolite abundances indicated that metabolic pathways are regulated as functional units, thereby simplifying adaptive responses. Our analysis demonstrates the potential for new scientific insight by integrating different types of large-scale experimental data from a single biological source.

Metabolomics guides rational development of a simplified cell culture medium for drug screening against Trypanosoma brucei

In vitro culture methods underpin many experimental approaches to biology and drug discovery. The modification of established cell culture methods to make them more biologically relevant or to optimize growth is traditionally a laborious task. Emerging metabolomic technology enables the rapid evaluation of intra- and extracellular metabolites and can be applied to the rational development of cell culture media. In this study, untargeted semiquantitative and targeted quantitative metabolomic analyses of fresh and spent media revealed the major nutritional requirements for the growth of bloodstream form Trypanosoma brucei. The standard culture medium (HMI11) contained unnecessarily high concentrations of 32 nutrients that were subsequently removed to make the concentrations more closely resemble those normally found in blood. Our new medium, Creek's minimal medium (CMM), supports in vitro growth equivalent to that in HMI11 and causes no significant perturbation of metabolite levels for 94% of the detected metabolome (<3-fold change; α = 0.05). Importantly, improved sensitivity was observed for drug activity studies in whole-cell phenotypic screenings and in the metabolomic mode of action assays. Four-hundred-fold 50% inhibitory concentration decreases were observed for pentamidine and methotrexate, suggesting inhibition of activity by nutrients present in HMI11. CMM is suitable for routine cell culture and offers important advantages for metabolomic studies and drug activity screening.

A rough guide to metabolite identification using high resolution liquid chromatography mass spectrometry in metabolomic profiling in metazoans

Compound identification in mass spectrometry based metabolomics can be a problem but sometimes the problem seems to be presented in an over complicated way. The current review focuses on metazoans where the range of metabolites is more restricted than for example in plants. The focus is on liquid chromatography with high resolution mass spectrometry where it is proposed that most of the problems in compound identification relate to structural isomers rather than to isobaric compounds. Thus many of the problems faced relate to separation of isomers, which is usually required even if fragmentation is used to support structural identification. Many papers report the use of MS/MS or MS² as an adjunct to the identification of known metabolites but there a few examples in metabolomics studies of metazoans of complete structure elucidation of novel metabolites or metabolites where no authentic standards are available for comparison.

LC-MS metabolomics from study design to data-analysis - using a versatile pathogen as a test case

Thanks to significant improvements in LC-MS technology, metabolomics is increasingly used as a tool to discriminate the responses of organisms to various stimuli or drugs. In this minireview we discuss all aspects of the LC-MS metabolomics pipeline, using a complex and versatile model organism, Leishmania donovani, as an illustrative example. The benefits of a hyphenated mass spectrometry platform and a detailed overview of the entire experimental pipeline from sampling, sample storage and sample list set-up to LC-MS measurements and the generation of meaningful results with state-of-the-art data-analysis software will be thoroughly discussed. Finally, we also highlight important pitfalls in the processing of LC-MS data and comment on the benefits of implementing metabolomics in a systems biology approach.

The 2-methylcitrate cycle is implicated in the detoxification of propionate in Toxoplasma gondii

Toxoplasma gondii belongs to the coccidian subgroup of the Apicomplexa phylum. The Coccidia are obligate intracellular pathogens that establish infection in their mammalian host via the enteric route. These parasites lack a mitochondrial pyruvate dehydrogenase complex but have preserved the degradation of branched-chain amino acids (BCAA) as a possible pathway to generate acetyl-CoA. Importantly, degradation of leucine, isoleucine and valine could lead to concomitant accumulation of propionyl-CoA, a toxic metabolite that inhibits cell growth. Like fungi and bacteria, the Coccidia possess the complete set of enzymes necessary to metabolize and detoxify propionate by oxidation to pyruvate via the 2-methylcitrate cycle (2-MCC). Phylogenetic analysis provides evidence that the 2-MCC was acquired via horizontal gene transfer. In T. gondii tachyzoites, this pathway is split between the cytosol and the mitochondrion. Although the rate-limiting enzyme 2-methylisocitrate lyase is dispensable for parasite survival, its substrates accumulate in parasites deficient in the enzyme and its absence confers increased sensitivity to propionic acid. BCAA is also dispensable in tachyzoites, leaving unresolved the source of mitochondrial acetyl-CoA.

Pyrimidine salvage in Trypanosoma brucei bloodstream forms and the trypanocidal action of halogenated pyrimidines

African trypanosomes are capable of both pyrimidine biosynthesis and salvage of preformed pyrimidines from the host. However, uptake of pyrimidines in bloodstream form trypanosomes has not been investigated, making it difficult to judge the relative importance of salvage and synthesis or to design a pyrimidine-based chemotherapy. Detailed characterization of pyrimidine transport activities in bloodstream form Trypanosoma brucei brucei found that these cells express a high-affinity uracil transporter (designated TbU3) that is clearly distinct from the procyclic pyrimidine transporters. This transporter had low affinity for uridine and 2'deoxyuridine and was the sole pyrimidine transporter expressed in these cells. In addition, thymidine was taken up inefficiently through a P1-type nucleoside transporter. Of importance, the anticancer drug 5-fluorouracil was an excellent substrate for TbU3, and several 5-fluoropyrimidine analogs were investigated for uptake and trypanocidal activity; 5F-orotic acid, 5F-2'deoxyuridine displayed activity in the low micromolar range. The metabolism and mode of action of these analogs was determined using metabolomic assessments of T. brucei clonal lines adapted to high levels of these pyrimidine analogs, and of the sensitive parental strains. The analysis showed that 5-fluorouracil is incorporated into a large number of metabolites but likely exerts toxicity through incorporation into RNA. 5F-2'dUrd and 5F-2'dCtd are not incorporated into nucleic acids but act as prodrugs by inhibiting thymidylate synthase as 5F-dUMP. We present the most complete model of pyrimidine salvage in T. brucei to date, supported by genome-wide profiling of the predicted pyrimidine biosynthesis and conversion enzymes.