MetMSLine: an automated and fully integrated pipeline for rapid processing of high-resolution LC-MS metabolomic datasets

MetMSLine represents a complete collection of functions in the R programming language as an accessible GUI for biomarker discovery in large-scale liquid-chromatography high-resolution mass spectral datasets from acquisition through to final metabolite identification forming a backend to output from any peak-picking software such as XCMS. MetMSLine automatically creates subdirectories, data tables and relevant figures at the following steps: (i) signal smoothing, normalization, filtration and noise transformation (PreProc.QC.LSC.R); (ii) PCA and automatic outlier removal (Auto.PCA.R); (iii) automatic regression, biomarker selection, hierarchical clustering and cluster ion/artefact identification (Auto.MV.Regress.R); (iv) Biomarker-MS/MS fragmentation spectra matching and fragment/neutral loss annotation (Auto.MS.MS.match.R) and (v) semi-targeted metabolite identification based on a list of theoretical masses obtained from public databases (DBAnnotate.R).

AVAILABILITY AND IMPLEMENTATION

All source code and suggested parameters are available in an un-encapsulated layout on http://wmbedmands.github.io/MetMSLine/. Readme files and a synthetic dataset of both X-variables (simulated LC-MS data), Y-variables (simulated continuous variables) and metabolite theoretical masses are also available on our GitHub repository.

Systems Biology Approaches Applied to Regenerative Medicine

Systems biology is the creation of theoretical and mathematical models for the study of biological systems, as an engine for hypothesis generation and to provide context to experimental data. It is underpinned by the collection and analysis of complex datasets from different biological systems, including global gene, RNA, protein and metabolite profiles. Regenerative medicine seeks to replace or repair tissues with compromised function (for example, through injury, deficiency or pathology), in order to improve their functionality. In this paper, we will address the application of systems biology approaches to the study of regenerative medicine, with a particular focus on approaches to study modifications to the genome, transcripts and small RNAs, proteins and metabolites.

A study of the effects of exercise on the urinary metabolome using normalisation to individual metabolic output

Aerobic exercise, in spite of its multi-organ benefit and potent effect on the metabolome, has yet to be investigated comprehensively via an untargeted metabolomics technology. We conducted an exploratory untargeted liquid chromatography mass spectrometry study to investigate the effects of a one-h aerobic exercise session in the urine of three physically active males. Individual urine samples were collected over a 37-h protocol (two pre-exercise and eight post-exercise). Raw data were subjected to a variety of normalization techniques, with the most effective measure dividing each metabolite by the sum response of that metabolite for each individual across the 37-h protocol expressed as a percentage. This allowed the metabolite responses to be plotted on a normalised scale. Our results highlight significant metabolites located in the following systems: purine pathway, tryptophan metabolism, carnitine metabolism, cortisol metabolism, androgen metabolism, amino acid oxidation, as well as metabolites from the gastrointestinal microbiome. Many of the significant changes observed in our pilot investigation mirror previous research studies, of various methodological designs, published within the last 15 years, although they have never been reported at the same time in a single study.

Metabolome searcher: a high throughput tool for metabolite identification and metabolic pathway mapping directly from mass spectrometry and using genome restriction

Background

Mass spectrometric analysis of microbial metabolism provides a long list of possible compounds. Restricting the identification of the possible compounds to those produced by the specific organism would benefit the identification process. Currently, identification of mass spectrometry (MS) data is commonly done using empirically derived compound databases. Unfortunately, most databases contain relatively few compounds, leaving long lists of unidentified molecules. Incorporating genome-encoded metabolism enables MS output identification that may not be included in databases. Using an organism’s genome as a database restricts metabolite identification to only those compounds that the organism can produce.

Results

To address the challenge of metabolomic analysis from MS data, a web-based application to directly search genome-constructed metabolic databases was developed. The user query returns a genome-restricted list of possible compound identifications along with the putative metabolic pathways based on the name, formula, SMILES structure, and the compound mass as defined by the user. Multiple queries can be done simultaneously by submitting a text file created by the user or obtained from the MS analysis software. The user can also provide parameters specific to the experiment’s MS analysis conditions, such as mass deviation, adducts, and detection mode during the query so as to provide additional levels of evidence to produce the tentative identification. The query results are provided as an HTML page and downloadable text file of possible compounds that are restricted to a specific genome. Hyperlinks provided in the HTML file connect the user to the curated metabolic databases housed in ProCyc, a Pathway Tools platform, as well as the KEGG Pathway database for visualization and metabolic pathway analysis.

Conclusions

Metabolome Searcher, a web-based tool, facilitates putative compound identification of MS output based on genome-restricted metabolic capability. This enables researchers to rapidly extend the possible identifications of large data sets for metabolites that are not in compound databases. Putative compound names with their associated metabolic pathways from metabolomics data sets are returned to the user for additional biological interpretation and visualization. This novel approach enables compound identification by restricting the possible masses to those encoded in the genome.

Bestatin induces specific changes in Trypanosoma cruzi dipeptide pool

Proteases and peptidases in Trypanosoma cruzi are considered potential targets for antichagasic chemotherapy. We monitored changes in low-mass metabolites in T. cruzi epimastigotes treated with bestatin, a dipeptide metalloaminopeptidase inhibitor. After treatment, multiple dipeptides were shown to be increased, confirming in situ inhibition of the leucine aminopeptidase of T. cruzi (LAPTc) and probably other peptidases.

Crystal structure of an arginase-like protein from Trypanosoma brucei that evolved without a binuclear manganese cluster

The X-ray crystal structure of an arginase-like protein from the parasitic protozoan Trypanosoma brucei, designated TbARG, is reported at 1.80 and 2.38 Å resolution in its reduced and oxidized forms, respectively. The oxidized form of TbARG is a disulfide-linked hexamer that retains the overall architecture of a dimer of trimers in the reduced form. Intriguingly, TbARG does not contain metal ions in its putative active site, and amino acid sequence comparisons indicate that all but one of the residues required for coordination to the catalytically obligatory binuclear manganese cluster in other arginases are substituted here with residues incapable of metal ion coordination. Therefore, the structure of TbARG is the first of a member of the arginase/deacetylase superfamily that is not a metalloprotein. Although we show that metal binding activity is easily reconstituted in TbARG by site-directed mutagenesis and confirmed in X-ray crystal structures, it is curious that this protein and its parasitic orthologues evolved away from metal binding function. Knockout of the TbARG gene from the genome demonstrated that its function is not essential to cultured bloodstream-form T. brucei, and metabolomics analysis confirmed that the enzyme has no role in the conversion of l-arginine to l-ornithine in these cells. While the molecular function of TbARG remains enigmatic, the fact that the T. brucei genome encodes only this protein and not a functional arginase indicates that the parasite must import l-ornithine from its host to provide a source of substrate for ornithine decarboxylase in the polyamine biosynthetic pathway, an active target for the development of antiparasitic drugs.

Rapid comparison of metabolites in humans and rats of different sexes using untargeted UPLC-TOFMS and an in-house software platform

Metabolite differences between sexes have rarely been observed in a global manner, but it has recently been made possible by the advancement in metabolomics techniques. In this study, untargeted ultraperformance liquid chromatography coupled to time-of-flight mass spectrometry and an in-house software platform were used for a rapid comparison of sex differences in urinary metabolites in humans and in urinary and serum metabolites in Sprague Dawley (SD) rats. In addition, the species differences of urinary metabolites between humans and SD rats were also observed. Principle component analysis showed that all the observed metabolite sex differences were more distinct in SD rats than in humans, indicating that the sex differences of human urinary metabolites is small compared with that of SD rats. In SD rats, the observed metabolite sex differences were more distinct in urine than in serum, indicating the importance of urine analysis for metabolomics studies. The species differences in the urinary metabolites of humans and SD rats were much more distinct than any of the observed sex differences. Many sex- and species-related markers were discovered and putatively identified. In both humans and SD rats, steroid metabolites appeared to constitute a major sex difference in urinary metabolites. This provides new proof of the special importance of steroid metabolites in sex differences from an untargeted metabolomics investigation, which is rare for sex differences. Contrary patterns involving adrenocortical activity appeared to exist between rodents and humans, which agrees with previous reports. In the serum metabolites of SD rats, sex differences in ascorbic acid or its isomer and pantothenic acid or its isomer, but not in steroid metabolites, were prominent. Human-specific α-N- phenylacetyl-l-glutamine and androsterone glucuronide were among the putative identities of the markers discriminating humans and SD rats. This study demonstrated the feasibility of an in-house software platform and provides metabolite-related information on sex and species differences.

Potential of mass spectrometry metabolomics for chemical food safety

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

Integrating proteomics profiling data sets: a network perspective

Understanding disease mechanisms often requires complex and accurate integration of cellular pathways and molecular networks. Systems biology offers the possibility to provide a comprehensive map of the cell's intricate wiring network, which can ultimately lead to decipher the disease phenotype. Here, we describe what biological pathways are, how they function in normal and abnormal cellular systems, limitations faced by databases for integrating data, and highlight how network models are emerging as a powerful integrative framework to understand and interpret the roles of proteins and peptides in diseases.

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.

WITHDRAWN: Recent advances in chemometric methods for plant metabolomics: A review

This article has been withdrawn at the request of the author(s) and/or editor. The Publisher apologizes for any inconvenience this may cause. The full Elsevier Policy on Article Withdrawal can be found at http://www.elsevier.com/locate/withdrawalpolicy.

Metabolomics in dyslipidemia

Hyperlipidemia is an important public health problem with increased incidence and prevalence worldwide. Current clinical biomarkers, triglyceride, total cholesterol, low-density lipoprotein cholesterol, and high-density lipoprotein cholesterol lack the necessary specificity and sensitivity and only increase significantly after serious dyslipidemia. Therefore, sensitive biomarkers are needed for hyperlipidemia. Hyperlipidemia-specific biomarkers would improve clinical diagnosis and therapeutic treatment at early disease stages. The aim of metabolomics is to identify untargeted and global small-molecule metabolite profiles from cells, biofluids, and tissues. This method offers the potential for a holistic approach to improve disease diagnoses and our understanding of underlying pathologic mechanisms. This review summarizes analytical techniques, data collection and analysis for metabolomics, and metabolomics in hyperlipidemia animal models and clinical studies. Mechanisms of hypolipemia and antilipemic drug therapy are also discussed. Metabolomics provides a new opportunity to gain insight into metabolic profiling and pathophysiologic mechanisms of hyperlipidemia.

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.

Basics of mass spectrometry based metabolomics

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

Current advances in systems and integrative biology

Systems biology has gained a tremendous amount of interest in the last few years. This is partly due to the realization that traditional approaches focusing only on a few molecules at a time cannot describe the impact of aberrant or modulated molecular environments across a whole system. Furthermore, a hypothesis-driven study aims to prove or disprove its postulations, whereas a hypothesis-free systems approach can yield an unbiased and novel testable hypothesis as an end-result. This latter approach foregoes assumptions which predict how a biological system should react to an altered microenvironment within a cellular context, across a tissue or impacting on distant organs. Additionally, re-use of existing data by systematic data mining and re-stratification, one of the cornerstones of integrative systems biology, is also gaining attention. While tremendous efforts using a systems methodology have already yielded excellent results, it is apparent that a lack of suitable analytic tools and purpose-built databases poses a major bottleneck in applying a systematic workflow. This review addresses the current approaches used in systems analysis and obstacles often encountered in large-scale data analysis and integration which tend to go unnoticed, but have a direct impact on the final outcome of a systems approach. Its wide applicability, ranging from basic research, disease descriptors, pharmacological studies, to personalized medicine, makes this emerging approach well suited to address biological and medical questions where conventional methods are not ideal.

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.

Microbial metabolomics: innovation, application, insight

Most textbooks depict metabolism as a well understood housekeeping function of cells. However, organisms vary in their metabolic needs according to the specific niches they reside in and selective pressures encountered therein. Recent advances in analytical chemistry have begun to reveal an unexpected diversity in the composition, structure and regulation of metabolic networks. Here, we review key technological developments in the area of metabolism and their impact on our understanding of the fundamental roles of metabolism in cellular physiology.

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.

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.

Untargeted metabolomic analysis of miltefosine action in Leishmania infantum reveals changes to the internal lipid metabolism

There are many theories as to the mode of action of miltefosine against Leishmania including alterations to the membrane lipid content, induction of apoptosis and modulation of macrophage responses. Here we perform untargeted metabolomics to elucidate the metabolic changes involved in miltefosine action. Over 800 metabolites were detected, 10% of which were significantly altered after 3.75 h. Many of the changes related to an increase in alkane fragment and sugar release. Fragment release is synchronised with reactive oxygen species production, but native membrane phospholipids remain intact. Signs of DNA damage were also detected as were changes to the levels of some thiols and polyamines. After 5 h of miltefosine treatment the cells showed depleted levels of most metabolites, indicating that the cells' outer membrane integrity had become compromised and internal metabolites were escaping upon cell death. In miltefosine resistant cells, the drug was not internalised and the changes to the internal metabolite levels were not seen. In contrast, cells resistant to antimony (SbIII) had similar corresponding alterations to the levels of internal metabolites as wild-type cells. A detailed knowledge of the mode of action of miltefosine will be important to inform the design of combination therapies to combat leishmaniasis, something that the research community should be prioritising in the coming years.

Clinical proteomic biomarkers: relevant issues on study design & technical considerations in biomarker development

Biomarker research is continuously expanding in the field of clinical proteomics. A combination of different proteomic-based methodologies can be applied depending on the specific clinical context of use. Moreover, current advancements in proteomic analytical platforms are leading to an expansion of biomarker candidates that can be identified. Specifically, mass spectrometric techniques could provide highly valuable tools for biomarker research. Ideally, these advances could provide with biomarkers that are clinically applicable for disease diagnosis and/ or prognosis. Unfortunately, in general the biomarker candidates fail to be implemented in clinical decision making. To improve on this current situation, a well-defined study design has to be established driven by a clear clinical need, while several checkpoints between the different phases of discovery, verification and validation have to be passed in order to increase the probability of establishing valid biomarkers. In this review, we summarize the technical proteomic platforms that are available along the different stages in the biomarker discovery pipeline, exemplified by clinical applications in the field of bladder cancer biomarker research.

Identification and characterization of microbial biofilm communities associated with corroded oil pipeline surfaces

Microbially influenced corrosion (MIC) has long been implicated in the deterioration of carbon steel in oil and gas pipeline systems. The authors sought to identify and characterize sessile biofilm communities within a high-temperature oil production pipeline, and to compare the profiles of the biofilm community with those of the previously analyzed planktonic communities. Eubacterial and archaeal 16S rRNA sequences of DNA recovered from extracted pipeline pieces, termed 'cookies,' revealed the presence of thermophilic sulfidogenic anaerobes, as well as mesophilic aerobes. Electron microscopy and elemental analysis of cookies confirmed the presence of sessile cells and chemical constituents consistent with corrosive biofilms. Mass spectrometry of cookie acid washes identified putative hydrocarbon metabolites, while surface profiling revealed pitting and general corrosion damage. The results suggest that in an established closed system, the biofilm taxa are representative of the planktonic eubacterial and archaeal community, and that sampling and monitoring of the planktonic bacterial population can offer insight into biocorrosion activity. Additionally, hydrocarbon biodegradation is likely to sustain these communities. The importance of appropriate sample handling and storage procedures to oilfield MIC diagnostics is highlighted.

A Trypanosoma brucei kinesin heavy chain promotes parasite growth by triggering host arginase activity

BACKGROUND

In order to promote infection, the blood-borne parasite Trypanosoma brucei releases factors that upregulate arginase expression and activity in myeloid cells.

METHODOLOGY/PRINCIPAL FINDINGS

By screening a cDNA library of T. brucei with an antibody neutralizing the arginase-inducing activity of parasite released factors, we identified a Kinesin Heavy Chain isoform, termed TbKHC1, as responsible for this effect. Following interaction with mouse myeloid cells, natural or recombinant TbKHC1 triggered SIGN-R1 receptor-dependent induction of IL-10 production, resulting in arginase-1 activation concomitant with reduction of nitric oxide (NO) synthase activity. This TbKHC1 activity was IL-4Rα-independent and did not mirror M2 activation of myeloid cells. As compared to wild-type T. brucei, infection by TbKHC1 KO parasites was characterized by strongly reduced parasitaemia and prolonged host survival time. By treating infected mice with ornithine or with NO synthase inhibitor, we observed that during the first wave of parasitaemia the parasite growth-promoting effect of TbKHC1-mediated arginase activation resulted more from increased polyamine production than from reduction of NO synthesis. In late stage infection, TbKHC1-mediated reduction of NO synthesis appeared to contribute to liver damage linked to shortening of host survival time.

CONCLUSION

A kinesin heavy chain released by T. brucei induces IL-10 and arginase-1 through SIGN-R1 signaling in myeloid cells, which promotes early trypanosome growth and favors parasite settlement in the host. Moreover, in the late stage of infection, the inhibition of NO synthesis by TbKHC1 contributes to liver pathogenicity.

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.

CASMI-The Small Molecule Identification Process from a Birmingham Perspective

The Critical Assessment of Small Molecule Identification (CASMI) contest was developed to provide a systematic comparative evaluation of strategies applied for the annotation and identification of small molecules. The authors participated in eleven challenges in both category 1 (to deduce a molecular formula) and category 2 (to deduce a molecular structure) related to high resolution LC-MS data. For category 1 challenges, the PUTMEDID_LCMS workflows provided the correct molecular formula in nine challenges; the two incorrect submissions were related to a larger mass error in experimental data than expected or the absence of the correct molecular formula in a reference file applied in the PUTMEDID_LCMS workflows. For category 2 challenges, MetFrag was applied to construct in silico fragmentation data and compare with experimentally-derived MS/MS data. The submissions for three challenges were correct, and for eight challenges, the submissions were not correct; some submissions showed similarity to the correct structures, while others showed no similarity. The low number of correct submissions for category 2 was a result of applying the assumption that all chemicals were derived from biological samples and highlights the importance of knowing the origin of biological or chemical samples studied and the metabolites expected to be present to define the correct chemical space to search in annotation processes.

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.

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.

Computational mass spectrometry for small molecules

: The identification of small molecules from mass spectrometry (MS) data remains a major challenge in the interpretation of MS data. This review covers the computational aspects of identifying small molecules, from the identification of a compound searching a reference spectral library, to the structural elucidation of unknowns. In detail, we describe the basic principles and pitfalls of searching mass spectral reference libraries. Determining the molecular formula of the compound can serve as a basis for subsequent structural elucidation; consequently, we cover different methods for molecular formula identification, focussing on isotope pattern analysis. We then discuss automated methods to deal with mass spectra of compounds that are not present in spectral libraries, and provide an insight into de novo analysis of fragmentation spectra using fragmentation trees. In addition, this review shortly covers the reconstruction of metabolic networks using MS data. Finally, we list available software for different steps of the analysis pipeline.

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.

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.

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.

Using nanotopography and metabolomics to identify biochemical effectors of multipotency

It is emerging that mesenchymal stem cell (MSC) metabolic activity may be a key regulator of multipotency. The metabolome represents a "snapshot" of the stem cell phenotype, and therefore metabolic profiling could, through a systems biology approach, offer and highlight critical biochemical pathways for investigation. To date, however, it has remained difficult to undertake unbiased experiments to study MSC multipotency in the absence of strategies to retain multipotency without recourse to soluble factors that can add artifact to experiments. Here we apply a nanotopographical systems approach linked to metabolomics to regulate plasticity and demonstrate rapid metabolite reorganization, allowing rational selection of key biochemical targets of self-renewal (ERK1/2, LDL, and Jnk). We then show that these signaling effectors regulate functional multipotency.

mzMatch-ISO: an R tool for the annotation and relative quantification of isotope-labelled mass spectrometry data

MOTIVATION

Stable isotope-labelling experiments have recently gained increasing popularity in metabolomics studies, providing unique insights into the dynamics of metabolic fluxes, beyond the steady-state information gathered by routine mass spectrometry. However, most liquid chromatography-mass spectrometry data analysis software lacks features that enable automated annotation and relative quantification of labelled metabolite peaks. Here, we describe mzMatch-ISO, a new extension to the metabolomics analysis pipeline mzMatch.R.

RESULTS

Targeted and untargeted isotope profiling using mzMatch-ISO provides a convenient visual summary of the quality and quantity of labelling for every metabolite through four types of diagnostic plots that show (i) the chromatograms of the isotope peaks of each compound in each sample group; (ii) the ratio of mono-isotopic and labelled peaks indicating the fraction of labelling; (iii) the average peak area of mono-isotopic and labelled peaks in each sample group; and (iv) the trend in the relative amount of labelling in a predetermined isotopomer. To aid further statistical analyses, the values used for generating these plots are also provided as a tab-delimited file. We demonstrate the power and versatility of mzMatch-ISO by analysing a (13)C-labelled metabolome dataset from trypanosomal parasites.

AVAILABILITY

mzMatch.R and mzMatch-ISO are available free of charge from http://mzmatch.sourceforge.net and can be used on Linux and Windows platforms running the latest version of R.

CONTACT

rainer.breitling@manchester.ac.uk.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

MetabR: an R script for linear model analysis of quantitative metabolomic data

Background

Metabolomics is an emerging high-throughput approach to systems biology, but data analysis tools are lacking compared to other systems level disciplines such as transcriptomics and proteomics. Metabolomic data analysis requires a normalization step to remove systematic effects of confounding variables on metabolite measurements. Current tools may not correctly normalize every metabolite when the relationships between each metabolite quantity and fixed-effect confounding variables are different, or for the effects of random-effect confounding variables. Linear mixed models, an established methodology in the microarray literature, offer a standardized and flexible approach for removing the effects of fixed- and random-effect confounding variables from metabolomic data.

Findings

Here we present a simple menu-driven program, “MetabR”, designed to aid researchers with no programming background in statistical analysis of metabolomic data. Written in the open-source statistical programming language R, MetabR implements linear mixed models to normalize metabolomic data and analysis of variance (ANOVA) to test treatment differences. MetabR exports normalized data, checks statistical model assumptions, identifies differentially abundant metabolites, and produces output files to help with data interpretation. Example data are provided to illustrate normalization for common confounding variables and to demonstrate the utility of the MetabR program.

Conclusions

We developed MetabR as a simple and user-friendly tool for implementing linear mixed model-based normalization and statistical analysis of targeted metabolomic data, which helps to fill a lack of available data analysis tools in this field. The program, user guide, example data, and any future news or updates related to the program may be found at http://metabr.r-forge.r-project.org/.

Stable isotope-assisted metabolomics for network-wide metabolic pathway elucidation

The combination of high-resolution LC–MS-based untargeted metabolomics with stable isotope tracing provides a global overview of the cellular fate of precursor metabolites. This methodology enables detection of putative metabolites from biological samples and simultaneous quantification of the pattern and extent of isotope labeling. Labeling of Trypanosoma brucei cell cultures with 50% uniformly ¹³C-labeled glucose demonstrated incorporation of glucose-derived carbon into 187 of 588 putatively identified metabolites in diverse pathways including carbohydrate, nucleotide, lipid, and amino acid metabolism. Labeling patterns confirmed the metabolic pathways responsible for the biosynthesis of many detected metabolites, and labeling was detected in unexpected metabolites, including two higher sugar phosphates annotated as octulose phosphate and nonulose phosphate. This untargeted approach to stable isotope tracing facilitates the biochemical analysis of known pathways and yields rapid identification of previously unexplored areas of metabolism.

Metabolomics in food science

Metabolomics, the newest member of the omics techniques, has become an important tool in agriculture, pharmacy, and environmental sciences. Advances in compound extraction, separation, detection, identification, and data analysis have allowed metabolomics applications in food sciences including food processing, quality, and safety. This chapter discusses recent advances and applications of metabolomics in food science.