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

Investigation of the threonine metabolism of Echinococcus multilocularis: The threonine dehydrogenase as a potential drug target in alveolar echinococcosis

Alveolar echinococcosis (AE) is a severe zoonotic disease caused by the metacestode stage of the fox tapeworm Echinococcus multilocularis. We recently showed that E. multilocularis metacestode vesicles scavenge large amounts of L-threonine from the culture medium. This motivated us to study the effect of L-threonine on the parasite and how it is metabolized. We established a novel metacestode vesicle growth assay with an automated readout, which showed that L-threonine treatment led to significantly increased parasite growth. In addition, L-threonine increased the formation of novel metacestode vesicles from primary parasite cell cultures in contrast to the non-proteinogenic threonine analog 3-hydroxynorvaline. Tracing of [U-13C]-L-threonine and metabolites in metacestode vesicles and culture medium resulted in the detection of [U-13C]-labeling in aminoacetone and glycine, indicating that L-threonine was metabolized by threonine dehydrogenase (TDH). EmTDH-mediated threonine metabolism in the E. multilocularis metacestode stage was further confirmed by quantitative real-time PCR, which demonstrated high expression of emtdh in in vitro cultured metacestode vesicles and also in metacestode samples obtained from infected animals. EmTDH was enzymatically active in metacestode vesicle extracts. The compounds disulfiram, myricetin, quercetin, sanguinarine, and seven quinazoline carboxamides were evaluated for their ability to inhibit recombinantly expressed EmTDH. The most potent inhibitors, albeit not very strong or highly specific, were disulfiram, myricetin and sanguinarine. These compounds were subsequently tested for activity against E. multilocularis metacestode vesicles and primary parasite cells and only sanguinarine demonstrated significant in vitro activity. However, TDH is not its only cellular target, and it is also known to be highly toxic. Our findings suggest that additional targets of sanguinarine should be explored, and that it may serve as a foundation for developing more specific compounds against the parasite. Moreover, the EmTDH assay could be a valuable high-throughput, target-based platform for discovering novel anti-echinococcal compounds.

Annotation of Metabolites in Stable Isotope Tracing Untargeted Metabolomics via Khipu-web

Stable isotope tracing is a crucial technique for understanding the metabolic wiring of biological systems, determining metabolic flux through pathways of interest, and detecting novel metabolites and pathways. Despite the potential insights provided by this technique, its application remains limited to a small number of targeted molecules and pathways. Because previous software tools usually require chemical formulas to find relevant features, and the data are highly complex, especially in untargeted metabolomics and when the downstream reactions and metabolites are poorly characterized. We report here Khipu version 2 and its new user-friendly web application. New functions are added to enhance analyzing stable isotope tracing data including metrics that evaluate peak enrichment in labeled samples, scoring methods to facilitate robust detection of intensity patterns and integrated natural abundance correction. We demonstrate that this approach can be applied to untargeted metabolomics to systematically extract isotope-labeled compounds and annotate the unidentified metabolites.

Detection of Inverse Stable Isotopic Labeling in Untargeted Metabolomic Data

Stable isotopic labeling is a powerful tool for determining the biosynthetic origin of metabolites and for discovering natural products that incorporate precursors of interest. When isotopically substituted precursors are not available commercially or synthetically, inverse stable isotopic labeling (InverSIL) is a useful alternative. With InverSIL, an organism is grown on an isotopically substituted medium and then fed precursors of natural isotopic abundance which can be tracked by mass spectrometry, thereby bypassing issues with precursor availability. Currently, there is no automated way to identify precursor incorporation in untargeted metabolomic data using InverSIL without specifying an expected change in the mass-to-charge ratio of metabolites that have incorporated the precursor. This makes it difficult to identify unknown natural products that may incorporate portions of precursors of interest using new biochemistry or to rapidly identify incorporation of multiple precursors into different metabolites simultaneously. To address this, we developed a new, robust workflow for the automated identification of inverse labeling in untargeted metabolomic data. We then use this method to identify metabolites that incorporate para-aminobenzoic acid and different portions of l-methionine, including in the same sample, and in the process discover the likely biosynthetic origin for the C-7 and C-9 methyl groups of the pterin portion of dephosphotetrahydromethanopterin, a C1 transfer coenzyme used by methylotrophic bacteria. This workflow can be applied in the future to streamline the use of the versatile InverSIL approach for natural product and metabolism research.

Bioengineered niches that recreate physiological extracellular matrix organisation to support long-term haematopoietic stem cells

Long-term reconstituting haematopoietic stem cells (LT-HSCs) are used to treat blood disorders via stem cell transplantation. The very low abundance of LT-HSCs and their rapid differentiation during in vitro culture hinders their clinical utility. Previous developments using stromal feeder layers, defined media cocktails, and bioengineering have enabled HSC expansion in culture, but of mostly short-term HSCs and progenitor populations at the expense of naive LT-HSCs. Here, we report the creation of a bioengineered LT-HSC maintenance niche that recreates physiological extracellular matrix organisation, using soft collagen type-I hydrogels to drive nestin expression in perivascular stromal cells (PerSCs). We demonstrate that nestin, which is expressed by HSC-supportive bone marrow stromal cells, is cytoprotective and, via regulation of metabolism, is important for HIF-1α expression in PerSCs. When CD34+ve HSCs were added to the bioengineered niches comprising nestin/HIF-1α expressing PerSCs, LT-HSC numbers were maintained with normal clonal and in vivo reconstitution potential, without media supplementation. We provide proof-of-concept that our bioengineered niches can support the survival of CRISPR edited HSCs. Successful editing of LT-HSCs ex vivo can have potential impact on the treatment of blood disorders.

SIMPEL: using stable isotopes to elucidate dynamics of context specific metabolism

The capacity to leverage high resolution mass spectrometry (HRMS) with transient isotope labeling experiments is an untapped opportunity to derive insights on context-specific metabolism, that is difficult to assess quantitatively. Tools are needed to comprehensively mine isotopologue information in an automated, high-throughput way without errors. We describe a tool, Stable Isotope-assisted Metabolomics for Pathway Elucidation (SIMPEL), to simplify analysis and interpretation of isotope-enriched HRMS datasets. The efficacy of SIMPEL is demonstrated through examples of central carbon and lipid metabolism. In the first description, a dual-isotope labeling experiment is paired with SIMPEL and isotopically nonstationary metabolic flux analysis (INST-MFA) to resolve fluxes in central metabolism that would be otherwise challenging to quantify. In the second example, SIMPEL was paired with HRMS-based lipidomics data to describe lipid metabolism based on a single labeling experiment. Available as an R package, SIMPEL extends metabolomics analyses to include isotopologue signatures necessary to quantify metabolic flux.

The bloodstream form of Trypanosoma brucei displays non-canonical gluconeogenesis

Trypanosoma brucei is a causative agent of the Human and Animal African Trypanosomiases. The mammalian stage parasites infect various tissues and organs including the bloodstream, central nervous system, skin, adipose tissue and lungs. They rely on ATP produced in glycolysis, consuming large amounts of glucose, which is readily available in the mammalian host. In addition to glucose, glycerol can also be used as a source of carbon and ATP and as a substrate for gluconeogenesis. However, the physiological relevance of glycerol-fed gluconeogenesis for the mammalian-infective life cycle forms remains elusive. To demonstrate its (in)dispensability, first we must identify the enzyme(s) of the pathway. Loss of the canonical gluconeogenic enzyme, fructose-1,6-bisphosphatase, does not abolish the process hence at least one other enzyme must participate in gluconeogenesis in trypanosomes. Using a combination of CRISPR/Cas9 gene editing and RNA interference, we generated mutants for four enzymes potentially capable of contributing to gluconeogenesis: fructose-1,6-bisphoshatase, sedoheptulose-1,7-bisphosphatase, phosphofructokinase and transaldolase, alone or in various combinations. Metabolomic analyses revealed that flux through gluconeogenesis was maintained irrespective of which of these genes were lost. Our data render unlikely a previously hypothesised role of a reverse phosphofructokinase reaction in gluconeogenesis and preclude the participation of a novel biochemical pathway involving transaldolase in the process. The sustained metabolic flux in gluconeogenesis in our mutants, including a triple-null strain, indicates the presence of a unique enzyme participating in gluconeogenesis. Additionally, the data provide new insights into gluconeogenesis and the pentose phosphate pathway, and improve the current understanding of carbon metabolism of the mammalian-infective stages of T. brucei.

CDK4/6 inhibitor-mediated cell overgrowth triggers osmotic and replication stress to promote senescence

Abnormal increases in cell size are associated with senescence and cell cycle exit. The mechanisms by which overgrowth primes cells to withdraw from the cell cycle remain unknown. We address this question using CDK4/6 inhibitors, which arrest cells in G0/G1 and are licensed to treat advanced HR+/HER2- breast cancer. We demonstrate that CDK4/6-inhibited cells overgrow during G0/G1, causing p38/p53/p21-dependent cell cycle withdrawal. Cell cycle withdrawal is triggered by biphasic p21 induction. The first p21 wave is caused by osmotic stress, leading to p38- and size-dependent accumulation of p21. CDK4/6 inhibitor washout results in some cells entering S-phase. Overgrown cells experience replication stress, resulting in a second p21 wave that promotes cell cycle withdrawal from G2 or the subsequent G1. We propose that the levels of p21 integrate signals from overgrowth-triggered stresses to determine cell fate. This model explains how hypertrophy can drive senescence and why CDK4/6 inhibitors have long-lasting effects in patients.

Program for Integration and Rapid Analysis of Mass Isotopomer Distributions (PIRAMID)

SUMMARY

The analysis of stable isotope labeling experiments requires accurate, efficient, and reproducible quantification of mass isotopomer distributions (MIDs), which is not a core feature of general-purpose metabolomics software tools that are optimized to quantify metabolite abundance. Here, we present PIRAMID (Program for Integration and Rapid Analysis of Mass Isotopomer Distributions), a MATLAB-based tool that addresses this need by offering a user-friendly, graphical user interface-driven program to automate the extraction of isotopic information from mass spectrometry (MS) datasets. This tool can simultaneously extract ion chromatograms for various metabolites from multiple data files in common vendor-agnostic file formats, locate chromatographic peaks based on a targeted list of characteristic ions and retention times, and integrate MIDs for each target ion. These MIDs can be corrected for natural isotopic background based on the user-defined molecular formula of each ion. PIRAMID offers support for datasets acquired from low- or high-resolution MS, and single (MS) or tandem (MS/MS) instruments. It also enables the analysis of single or dual labeling experiments using a variety of isotopes (i.e. 2H, 13C, 15N, 18O, 34S).

DATA AVAILABILITY AND IMPLEMENTATION

MATLAB p-code files are freely available for non-commercial use and can be downloaded from https://mfa.vueinnovations.com/. Commercial licenses are also available. All the data presented in this publication are available under the "Help_menu" folder of the PIRAMID software.

High-throughput Saccharomyces cerevisiae cultivation method for credentialing-based untargeted metabolomics

Identifying metabolites in model organisms is critical for many areas of biology, including unravelling disease aetiology or elucidating functions of putative enzymes. Even now, hundreds of predicted metabolic genes in Saccharomyces cerevisiae remain uncharacterized, indicating that our understanding of metabolism is far from complete even in well-characterized organisms. While untargeted high-resolution mass spectrometry (HRMS) enables the detection of thousands of features per analysis, many of these have a non-biological origin. Stable isotope labelling (SIL) approaches can serve as credentialing strategies to distinguish biologically relevant features from background signals, but implementing these experiments at large scale remains challenging. Here, we developed a SIL-based approach for high-throughput untargeted metabolomics in S. cerevisiae, including deep-48 well format-based cultivation and metabolite extraction, building on the peak annotation and verification engine (PAVE) tool. Aqueous and nonpolar extracts were analysed using HILIC and RP liquid chromatography, respectively, coupled to Orbitrap Q Exactive HF mass spectrometry. Of the approximately 37,000 total detected features, only 3-7% of the features were credentialed and used for data analysis with open-source software such as MS-DIAL, MetFrag, Shinyscreen, SIRIUS CSI:FingerID, and MetaboAnalyst, leading to the successful annotation of 198 metabolites using MS² database matching. Comparable metabolic profiles were observed for wild-type and sdh1Δ yeast strains grown in deep-48 well plates versus the classical shake flask format, including the expected increase in intracellular succinate concentration in the sdh1Δ strain. The described approach enables high-throughput yeast cultivation and credentialing-based untargeted metabolomics, providing a means to efficiently perform molecular phenotypic screens and help complete metabolic networks.

Generalized Tree Structure to Annotate Untargeted Metabolomics and Stable Isotope Tracing Data

In untargeted metabolomics, multiple ions are often measured for each original metabolite, including isotopic forms and in-source modifications, such as adducts and fragments. Without prior knowledge of the chemical identity or formula, computational organization and interpretation of these ions is challenging, which is the deficit of previous software tools that perform the task using network algorithms. We propose here a generalized tree structure to annotate ions in relationships to the original compound and infer neutral mass. An algorithm is presented to convert mass distance networks to this tree structure with high fidelity. This method is useful for both regular untargeted metabolomics and stable isotope tracing experiments. It is implemented as a Python package (khipu) and provides a JSON format for easy data exchange and software interoperability. By generalized preannotation, khipu makes it feasible to connect metabolomics data with common data science tools and supports flexible experimental designs.

Nanotopography reveals metabolites that maintain the immunomodulatory phenotype of mesenchymal stromal cells

Mesenchymal stromal cells (MSCs) are multipotent progenitor cells that are of considerable clinical potential in transplantation and anti-inflammatory therapies due to their capacity for tissue repair and immunomodulation. However, MSCs rapidly differentiate once in culture, making their large-scale expansion for use in immunomodulatory therapies challenging. Although the differentiation mechanisms of MSCs have been extensively investigated using materials, little is known about how materials can influence paracrine activities of MSCs. Here, we show that nanotopography can control the immunomodulatory capacity of MSCs through decreased intracellular tension and increasing oxidative glycolysis. We use nanotopography to identify bioactive metabolites that modulate intracellular tension, growth and immunomodulatory phenotype of MSCs in standard culture and during larger scale cell manufacture. Our findings demonstrate an effective route to support large-scale expansion of functional MSCs for therapeutic purposes.

Evaluating LC-HRMS metabolomics data processing software using FAIR principles for research software

BACKGROUND

Liquid chromatography-high resolution mass spectrometry (LC-HRMS) is a popular approach for metabolomics data acquisition and requires many data processing software tools. The FAIR Principles - Findability, Accessibility, Interoperability, and Reusability - were proposed to promote open science and reusable data management, and to maximize the benefit obtained from contemporary and formal scholarly digital publishing. More recently, the FAIR principles were extended to include Research Software (FAIR4RS).

AIM OF REVIEW

This study facilitates open science in metabolomics by providing an implementation solution for adopting FAIR4RS in the LC-HRMS metabolomics data processing software. We believe our evaluation guidelines and results can help improve the FAIRness of research software.

KEY SCIENTIFIC CONCEPTS OF REVIEW

We evaluated 124 LC-HRMS metabolomics data processing software obtained from a systematic review and selected 61 software for detailed evaluation using FAIR4RS-related criteria, which were extracted from the literature along with internal discussions. We assigned each criterion one or more FAIR4RS categories through discussion. The minimum, median, and maximum percentages of criteria fulfillment of software were 21.6%, 47.7%, and 71.8%. Statistical analysis revealed no significant improvement in FAIRness over time. We identified four criteria covering multiple FAIR4RS categories but had a low %fulfillment: (1) No software had semantic annotation of key information; (2) only 6.3% of evaluated software were registered to Zenodo and received DOIs; (3) only 14.5% of selected software had official software containerization or virtual machine; (4) only 16.7% of evaluated software had a fully documented functions in code. According to the results, we discussed improvement strategies and future directions.

Generalized tree structure to annotate untargeted metabolomics and stable isotope tracing data

In untargeted metabolomics, multiple ions are often measured for each original metabolite, including isotopic forms and in-source modifications, such as adducts and fragments. Without prior knowledge of the chemical identity or formula, computational organization and interpretation of these ions is challenging, which is the deficit of previous software tools that perform the task using network algorithms. We propose here a generalized tree structure to annotate ions to relationships to the original compound and infer neutral mass. An algorithm is presented to convert mass distance networks to this tree structure with high fidelity. This method is useful for both regular untargeted metabolomics and stable isotope tracing experiments. It is implemented as a Python package (khipu), and provides a JSON format for easy data exchange and software interoperability. By generalized pre-annotation, khipu makes it feasible to connect metabolomics data with common data science tools, and supports flexible experimental designs.

Metabolomics Applied to Cyanobacterial Toxins and Natural Products

The biological and chemical diversity of Cyanobacteria is remarkable. These ancient prokaryotes are widespread in nature and can be found in virtually every habitat on Earth where there is light and water. They are producers of an array of secondary metabolites with important ecological roles, toxic effects, and biotechnological applications. The investigation of cyanobacterial metabolites has benefited from advances in analytical tools and bioinformatics that are employed in metabolomic analyses. In this chapter, we review selected articles highlighting the use of targeted and untargeted metabolomics in the analyses of secondary metabolites produced by cyanobacteria. Here, cyanobacterial secondary metabolites have been didactically divided into toxins and natural products according to their relevance to toxicological studies and drug discovery, respectively. This review illustrates how metabolomics has improved the chemical analysis of cyanobacteria in terms of speed, sensitivity, selectivity, and/or coverage, allowing for broader and more complex scientific questions.

Global stable-isotope tracing metabolomics reveals system-wide metabolic alternations in aging Drosophila

System-wide metabolic homeostasis is crucial for maintaining physiological functions of living organisms. Stable-isotope tracing metabolomics allows to unravel metabolic activity quantitatively by measuring the isotopically labeled metabolites, but has been largely restricted by coverage. Delineating system-wide metabolic homeostasis at the whole-organism level remains challenging. Here, we develop a global isotope tracing metabolomics technology to measure labeled metabolites with a metabolome-wide coverage. Using Drosophila as an aging model organism, we probe the in vivo tracing kinetics with quantitative information on labeling patterns, extents and rates on a metabolome-wide scale. We curate a system-wide metabolic network to characterize metabolic homeostasis and disclose a system-wide loss of metabolic coordinations that impacts both intra- and inter-tissue metabolic homeostasis significantly during Drosophila aging. Importantly, we reveal an unappreciated metabolic diversion from glycolysis to serine metabolism and purine metabolism as Drosophila aging. The developed technology facilitates a system-level understanding of metabolic regulation in living organisms.

An optimization method for untargeted MS-based isotopic tracing investigations of metabolism

INTRODUCTION

Stable isotope tracer studies are increasingly applied to explore metabolism from the detailed analysis of tracer incorporation into metabolites. Untargeted LC/MS approaches have recently emerged and provide potent methods for expanding the dimension and complexity of the metabolic networks that can be investigated. A number of software tools have been developed to process the highly complex MS data collected in such studies; however, a method to optimize the extraction of valuable isotopic data is lacking.

OBJECTIVES

To develop and validate a method to optimize automated data processing for untargeted MS-based isotopic tracing investigations of metabolism.

METHODS

The method is based on the application of a suitable reference material to rationally perform parameter optimization throughout the complete data processing workflow. It was applied in the context of ¹³C-labelling experiments and with two different software, namely geoRge and X13CMS. It was illustrated with the study of a E. coli mutant impaired for central metabolism.

RESULTS

The optimization methodology provided significant gain in the number and quality of extracted isotopic data, independently of the software considered. Pascal triangle samples are well suited for such purpose since they allow both the identification of analytical issues and optimization of data processing at the same time.

CONCLUSION

The proposed method maximizes the biological value of untargeted MS-based isotopic tracing investigations by revealing the full metabolic information that is encoded in the labelling patterns of metabolites.

Global Tracking of Transformation Products of Environmental Contaminants by 2H-Labeled Stable Isotope-Assisted Metabolomics

Stable isotope-assisted metabolomics (SIAM) enables global tracking of isotopic labels in nontargeted metabolomics in living organisms. However, its application in tracking transformation products (TPs, as metabolites of contaminants) of environmental contaminants is still a challenge due to limits in methodology, unmatured algorithms, and the high cost of ¹³C-labeled contaminants. Therefore, we developed a ²H-SIAM pipeline coupled with a highly flexible algorithm ²H-SIAM(1.0) (https://github.com/kechen1984/2H-SIAM), facilitating tracking TPs of contaminants in the environmental matrix. A detailed discussion illustrates the theory, behavior, and prospect of ²H-SIAM. We demonstrate that the proposed ²H-SIAM pipeline has unique advantages over ¹³C-SIAM, for example, cost-effective ²H-labeled contaminants, easy synthesis of ²H-labeled emerging contaminants, and providing more structural information. A pyrene soil degradation study further confirmed its high performance. It efficiently discarded 99% of noise signals and extracted 52 features from the nontargeted high resolution mass spectrometry (HRMS) data. Among them, 13 features were annotated as TPs of pyrene with identification confidence from Level 2a to Level 5, and 5 TPs were reported for the first time. In conclusion, the proposed ²H-SIAM pipeline is powerful in tracking potential TPs of environmental contaminants with unique advantages.

An isotopic labeling approach linking natural products with biosynthetic gene clusters

Major advances in genome sequencing and large-scale biosynthetic gene cluster (BGC) analysis have prompted an age of natural product discovery driven by genome mining. Still, connecting molecules to their cognate BGCs is a substantial bottleneck for this approach. We have developed a mass-spectrometry-based parallel stable isotope labeling platform, termed IsoAnalyst, which assists in associating metabolite stable isotope labeling patterns with BGC structure prediction to connect natural products to their corresponding BGCs. Here we show that IsoAnalyst can quickly associate both known metabolites and unknown analytes with BGCs to elucidate the complex chemical phenotypes of these biosynthetic systems. We validate this approach for a range of compound classes, using both the type strain Saccharopolyspora erythraea and an environmentally isolated Micromonospora sp. We further demonstrate the utility of this tool with the discovery of lobosamide D, a new and structurally unique member of the family of lobosamide macrolactams.

MS-IDF: A Software Tool for Nontargeted Identification of Endogenous Metabolites after Chemical Isotope Labeling Based on a Narrow Mass Defect Filter

Chemical isotope labeling liquid chromatography mass spectrometry (LC-MS) is an emerging metabolomic strategy for the quantification and characterization of small molecular compounds in biological samples. However, its subsequent data analysis is not straightforward due to a large amount of data produced and interference of biological matrices. In order to improve the efficiency of searching and identification of target endogenous metabolites, a new software tool for nontargeted metabolomics data processing called MS-IDF was developed based on the principle of a narrow mass defect filter. The developed tool provided two function modules, including IsoFinder and MDFinder. The IsoFinder function module applied a conventional peak extraction method by using a fixed mass differences between the heavy and light labels and by the alignment of chromatographic retention time (RT). On the other hand, MDFinder was designed to incorporate the accurate mass defect differences between or among stable isotopes in the peak extraction process. By setting an appropriate filter interval, the target metabolites can be efficiently screened out while eliminating interference. Notably, the present results showed that the efficiency in compound identification using the new MDFinder module was nearly doubled as compared to the conventional IsoFinder method (an increase from 259 to 423 compounds). The Matlab codes of the developed MS-IDF software are available from github at https://github.com/jydong2018/MS_IDF. Based on the MS-IDF software tool, a novel and effective approach from nontargeted to targeted metabolomics research was developed and applied to the exploration of potential primary amine biomarkers in patients with schizophrenia. With this approach, potential biomarkers, including N,N-dimethylglycine, S-adenosine-l-methionine, dl-homocysteine, and spermidine, were discovered.

Approaches for completing metabolic networks through metabolite damage and repair discovery

Metabolites are prone to damage, either via enzymatic side reactions, which collectively form the underground metabolism, or via spontaneous chemical reactions. The resulting non-canonical metabolites that can be toxic, are mended by dedicated "metabolite repair enzymes." Deficiencies in the latter can cause severe disease in humans, whereas inclusion of repair enzymes in metabolically engineered systems can improve the production yield of value-added chemicals. The metabolite damage and repair loops are typically not yet included in metabolic reconstructions and it is likely that many remain to be discovered. Here, we review strategies and associated challenges for unveiling non-canonical metabolites and metabolite repair enzymes, including systematic approaches based on high-resolution mass spectrometry, metabolome-wide side-activity prediction, as well as high-throughput substrate and phenotypic screens.

Depletion of a Toxoplasma porin leads to defects in mitochondrial morphology and contacts with the endoplasmic reticulum

The voltage-dependent anion channel (VDAC) is a ubiquitous channel in the outer membrane of the mitochondrion with multiple roles in protein, metabolite and small molecule transport. In mammalian cells, VDAC protein, as part of a larger complex including the inositol triphosphate receptor, has been shown to have a role in mediating contacts between the mitochondria and endoplasmic reticulum (ER). We identify VDAC of the pathogenic apicomplexan Toxoplasma gondii and demonstrate its importance for parasite growth. We show that VDAC is involved in protein import and metabolite transfer to mitochondria. Further, depletion of VDAC resulted in significant morphological changes in the mitochondrion and ER, suggesting a role in mediating contacts between these organelles in T. gondii.

This article has an associated First Person interview with the first author of the paper.

Summary: Depletion of the Toxoplasma voltage-dependent anion channel highlights the importance of endoplasmic reticulum–mitochondria membrane contact sites in maintaining organelle morphology.

Divergent metabolism between Trypanosoma congolense and Trypanosoma brucei results in differential sensitivity to metabolic inhibition

Animal African Trypanosomiasis (AAT) is a debilitating livestock disease prevalent across sub-Saharan Africa, a main cause of which is the protozoan parasite Trypanosoma congolense. In comparison to the well-studied T. brucei, there is a major paucity of knowledge regarding the biology of T. congolense. Here, we use a combination of omics technologies and novel genetic tools to characterise core metabolism in T. congolense mammalian-infective bloodstream-form parasites, and test whether metabolic differences compared to T. brucei impact upon sensitivity to metabolic inhibition. Like the bloodstream stage of T. brucei, glycolysis plays a major part in T. congolense energy metabolism. However, the rate of glucose uptake is significantly lower in bloodstream stage T. congolense, with cells remaining viable when cultured in concentrations as low as 2 mM. Instead of pyruvate, the primary glycolytic endpoints are succinate, malate and acetate. Transcriptomics analysis showed higher levels of transcripts associated with the mitochondrial pyruvate dehydrogenase complex, acetate generation, and the glycosomal succinate shunt in T. congolense, compared to T. brucei. Stable-isotope labelling of glucose enabled the comparison of carbon usage between T. brucei and T. congolense, highlighting differences in nucleotide and saturated fatty acid metabolism. To validate the metabolic similarities and differences, both species were treated with metabolic inhibitors, confirming that electron transport chain activity is not essential in T. congolense. However, the parasite exhibits increased sensitivity to inhibition of mitochondrial pyruvate import, compared to T. brucei. Strikingly, T. congolense exhibited significant resistance to inhibitors of fatty acid synthesis, including a 780-fold higher EC50 for the lipase and fatty acid synthase inhibitor Orlistat, compared to T. brucei. These data highlight that bloodstream form T. congolense diverges from T. brucei in key areas of metabolism, with several features that are intermediate between bloodstream- and insect-stage T. brucei. These results have implications for drug development, mechanisms of drug resistance and host-pathogen interactions.

β-Adrenoceptor regulation of metabolism in U937 derived macrophages

Macrophages have important roles in the immune system including clearing pathogens and wound healing. Metabolic phenotypes in macrophages have been associated with functional phenotypes, where pro-inflammatory macrophages have an increased rate of glycolysis and anti-inflammatory macrophages primarily use oxidative phosphorylation. β-adrenoceptor (βAR) signalling in macrophages has been implicated in disease states such as cancer, atherosclerosis and rheumatoid arthritis. The impact of βAR signalling on macrophage metabolism has not been defined. Using metabolomics and proteomics, we describe the impact of βAR signalling on macrophages treated with isoprenaline. We found that βAR signalling alters proteins involved in cytoskeletal rearrangement and redox homeostasis of the cell. We showed that βAR signalling in macrophages shifts glucose metabolism from glycolysis towards the tricarboxylic acid cycle and pentose phosphate pathways. We also show that βAR signalling perturbs purine metabolism by accumulating adenylate and guanylate pools. Taken together, these results indicate that βAR signalling shifts metabolism to support redox processes and upregulates proteins involved in cytoskeletal changes, which may contribute to βAR effects on macrophage function.

Plasmodium falciparum LipB mutants display altered redox and carbon metabolism in asexual stages and cannot complete sporogony in Anopheles mosquitoes

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Apicoplast LipB deletion leads to changed antioxidant expression that precedes and coincides with accelerated differentiation.

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3D7 Plasmodium exhibits changes in glycolysis and tricarboxylic acid cycle activity after deletion of apicoplast LipB.

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When LipB is deleted from NF54 Plasmodium, the resulting parasites cannot complete their development in mosquitoes.

Malaria is still one of the most important global infectious diseases. Emergence of drug resistance and a shortage of new efficient antimalarials continue to hamper a malaria eradication agenda. Malaria parasites are highly sensitive to changes in the redox environment. Understanding the mechanisms regulating parasite redox could contribute to the design of new drugs. Malaria parasites have a complex network of redox regulatory systems housed in their cytosol, in their mitochondrion and in their plastid (apicoplast). While the roles of enzymes of the thioredoxin and glutathione pathways in parasite survival have been explored, the antioxidant role of α-lipoic acid (LA) produced in the apicoplast has not been tested. To take a first step in teasing a putative role of LA in redox regulation, we analysed a mutant Plasmodium falciparum (3D7 strain) lacking the apicoplast lipoic acid protein ligase B (lipB) known to be depleted of LA. Our results showed a change in expression of redox regulators in the apicoplast and the cytosol. We further detected a change in parasite central carbon metabolism, with lipB deletion resulting in changes to glycolysis and tricarboxylic acid cycle activity. Further, in another Plasmodium cell line (NF54), deletion of lipB impacted development in the mosquito, preventing the detection of infectious sporozoite stages. While it is not clear at this point if the observed phenotypes are linked, these findings flag LA biosynthesis as an important subject for further study in the context of redox regulation in asexual stages, and point to LipB as a potential target for the development of new transmission drugs.

The Comprehensive and Reliable Detection of Secondary Metabolites in Trichoderma reesei: A Tool for the Discovery of Novel Substances

A method based on reversed phase high-performance liquid chromatography coupled with electrospray ionization high-resolution mass spectrometry (RP-HPLC-ESI-HRMS) for the comprehensive and reliable detection of secondary metabolites of Trichoderma reesei cultured in synthetic minimal liquid medium is presented. A stable isotope-assisted (SIA) workflow is used, which allows the automated, comprehensive extraction of truly fungal metabolite-derived LC-MS signals from the acquired chromatographic data. The subsequent statistical data analysis and a typical outcome of such a metabolomics data evaluation are shown by way of example in a previously published study on the influence of the pleiotropic regulator transcription factor Xylanase promoter binding protein 1 (Xpp1) in T. reesei on secondary metabolism.

Untargeted high-resolution paired mass distance data mining for retrieving general chemical relationships

Untargeted metabolomics analysis captures chemical reactions among small molecules. Common mass spectrometry-based metabolomics workflows first identify the small molecules significantly associated with the outcome of interest, then begin exploring their biochemical relationships to understand biological fate or impact. We suggest an alternative by which general chemical relationships including abiotic reactions can be directly retrieved through untargeted high-resolution paired mass distance (PMD) analysis without a priori knowledge of the identities of participating compounds. PMDs calculated from the mass spectrometry data are linked to chemical reactions obtained via data mining of small molecule and reaction databases, i.e. 'PMD-based reactomics'. We demonstrate applications of PMD-based reactomics including PMD network analysis, source appointment of unknown compounds, and biomarker reaction discovery as complements to compound discovery analyses used in traditional untargeted workflows. An R implementation of reactomics analysis and the reaction/PMD databases is available as the pmd package.

Tracking the carbons supplying gluconeogenesis

As the burden of type 2 diabetes mellitus (T2DM) grows in the 21st century, the need to understand glucose metabolism heightens. Increased gluconeogenesis is a major contributor to the hyperglycemia seen in T2DM. Isotope tracer experiments in humans and animals over several decades have offered insights into gluconeogenesis under euglycemic and diabetic conditions. This review focuses on the current understanding of carbon flux in gluconeogenesis, including substrate contribution of various gluconeogenic precursors to glucose production. Alterations of gluconeogenic metabolites and fluxes in T2DM are discussed. We also highlight ongoing knowledge gaps in the literature that require further investigation. A comprehensive analysis of gluconeogenesis may enable a better understanding of T2DM pathophysiology and identification of novel targets for treating hyperglycemia.

Multi-omics analysis delineates the distinct functions of sub-cellular acetyl-CoA pools in Toxoplasma gondii

BACKGROUND

Acetyl-CoA is a key molecule in all organisms, implicated in several metabolic pathways as well as in transcriptional regulation and post-translational modification. The human pathogen Toxoplasma gondii possesses at least four enzymes which generate acetyl-CoA in the nucleo-cytosol (acetyl-CoA synthetase (ACS); ATP citrate lyase (ACL)), mitochondrion (branched-chain α-keto acid dehydrogenase-complex (BCKDH)) and apicoplast (pyruvate dehydrogenase complex (PDH)). Given the diverse functions of acetyl-CoA, we know very little about the role of sub-cellular acetyl-CoA pools in parasite physiology.

RESULTS

To assess the importance and functions of sub-cellular acetyl-CoA-pools, we measured the acetylome, transcriptome, proteome and metabolome of parasites lacking ACL/ACS or BCKDH. We demonstrate that ACL/ACS constitute a synthetic lethal pair. Loss of both enzymes causes a halt in fatty acid elongation, hypo-acetylation of nucleo-cytosolic and secretory proteins and broad changes in gene expression. In contrast, loss of BCKDH results in an altered TCA cycle, hypo-acetylation of mitochondrial proteins and few specific changes in gene expression. We provide evidence that changes in the acetylome, transcriptome and proteome of cells lacking BCKDH enable the metabolic adaptations and thus the survival of these parasites.

CONCLUSIONS

Using multi-omics and molecular tools, we obtain a global and integrative picture of the role of distinct acetyl-CoA pools in T. gondii physiology. Cytosolic acetyl-CoA is essential and is required for the synthesis of parasite-specific fatty acids. In contrast, loss of mitochondrial acetyl-CoA can be compensated for through metabolic adaptations implemented at the transcriptional, translational and post-translational level.

Miso: an R package for multiple isotope labeling assisted metabolomics data analysis

MOTIVATION

The use of stable isotope labeling is highly advantageous for structure elucidation in metabolomics studies. However, computational tools dealing with multiple-precursor-based labeling studies are still missing. Hence, we developed Miso, an R package providing automated and efficient data analysis workflow to detect the complete repertoire of labeled molecules from multiple-precursor-based labeling experiments.

RESULTS

The capability of Miso is demonstrated by the analysis of liquid chromatography-mass spectrometry data obtained from duckweed plants fed with one unlabeled and two differently labeled tyrosine (unlabeled tyrosine, tyrosine-2H4 and tyrosine-13C915N1). The resulting data matrix generated by Miso contains sets of unlabeled and labeled ions with their retention time, m/z values and number of labeled atoms that can be directly utilized for database query and biological studies.

AVAILABILITY AND IMPLEMENTATION

Miso is publicly available on the CRAN repository (https://cran.r-project.org/web/packages/Miso). A reproducible case study and a detailed tutorial are available from GitHub (https://github.com/YonghuiDong/Miso_example).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

JUMPm: A Tool for Large-Scale Identification of Metabolites in Untargeted Metabolomics

Metabolomics is increasingly important for biomedical research, but large-scale metabolite identification in untargeted metabolomics is still challenging. Here, we present Jumbo Mass spectrometry-based Program of Metabolomics (JUMPm) software, a streamlined software tool for identifying potential metabolite formulas and structures in mass spectrometry. During database search, the false discovery rate is evaluated by a target-decoy strategy, where the decoys are produced by breaking the octet rule of chemistry. We illustrated the utility of JUMPm by detecting metabolite formulas and structures from liquid chromatography coupled tandem mass spectrometry (LC-MS/MS) analyses of unlabeled and stable-isotope labeled yeast samples. We also benchmarked the performance of JUMPm by analyzing a mixed sample from a commercially available metabolite library in both hydrophilic and hydrophobic LC-MS/MS. These analyses confirm that metabolite identification can be significantly improved by estimating the element composition in formulas using stable isotope labeling, or by introducing LC retention time during a spectral library search, which are incorporated into JUMPm functions. Finally, we compared the performance of JUMPm and two commonly used programs, Compound Discoverer 3.1 and MZmine 2, with respect to putative metabolite identifications. Our results indicate that JUMPm is an effective tool for metabolite identification of both unlabeled and labeled data in untargeted metabolomics.

Suramin exposure alters cellular metabolism and mitochondrial energy production in African trypanosomes

Introduced about a century ago, suramin remains a frontline drug for the management of early-stage East African trypanosomiasis (sleeping sickness). Cellular entry into the causative agent, the protozoan parasite Trypanosoma brucei, occurs through receptor-mediated endocytosis involving the parasite's invariant surface glycoprotein 75 (ISG75), followed by transport into the cytosol via a lysosomal transporter. The molecular basis of the trypanocidal activity of suramin remains unclear, but some evidence suggests broad, but specific, impacts on trypanosome metabolism (i.e. polypharmacology). Here we observed that suramin is rapidly accumulated in trypanosome cells proportionally to ISG75 abundance. Although we found little evidence that suramin disrupts glycolytic or glycosomal pathways, we noted increased mitochondrial ATP production, but a net decrease in cellular ATP levels. Metabolomics highlighted additional impacts on mitochondrial metabolism, including partial Krebs' cycle activation and significant accumulation of pyruvate, corroborated by increased expression of mitochondrial enzymes and transporters. Significantly, the vast majority of suramin-induced proteins were normally more abundant in the insect forms compared with the blood stage of the parasite, including several proteins associated with differentiation. We conclude that suramin has multiple and complex effects on trypanosomes, but unexpectedly partially activates mitochondrial ATP-generating activity. We propose that despite apparent compensatory mechanisms in drug-challenged cells, the suramin-induced collapse of cellular ATP ultimately leads to trypanosome cell death.

Evaluation of freely available software tools for untargeted quantification of 13C isotopic enrichment in cellular metabolome from HR-LC/MS data

¹³C Metabolic Flux Analysis (¹³C-MFA) involves the quantification of isotopic enrichment in cellular metabolites and fitting the resultant data to the metabolic network model of the organism. Coverage and resolution of the resultant flux map depends on the total number of metabolites and fragments in which ¹³C enrichment can be quantified accurately. Experimental techniques for tracking ¹³C enrichment are evolving rapidly and large volumes of data are now routinely generated through the use of Liquid Chromatography coupled with High-Resolution Mass Spectrometry (HR-LC/MS). Therefore, the current manuscript is focused on the challenges in high-throughput analyses of such large datasets. Current ¹³C-MFA studies often have to rely on the targeted quantification of a small subset of metabolites, thereby leaving a large fraction of the data unexplored. A number of public domain software tools have been reported in recent years for the untargeted quantitation of isotopic enrichment. However, the suitability of their application across diverse datasets has not been investigated. Here, we test the software tools X¹³CMS, DynaMet, geoRge, and HiResTEC with three diverse datasets. The tools provided a global, untargeted view of ¹³C enrichment in metabolites in all three datasets and a much-needed automation in data analysis. Some inconsistencies were observed in results obtained from the different tools, which could be partially ascribed to the lack of baseline separation and potential mass conflicts. After removing the false positives manually, isotopic enrichment could be quantified reliably in a large repertoire of metabolites. Of the software tools explored, geoRge and HiResTEC consistently performed well for the untargeted analysis of all datasets tested.

Integration of flux measurements and pharmacological controls to optimize stable isotope-resolved metabolomics workflows and interpretation

Stable isotope-resolved metabolomics (SIRM) provides information regarding the relative activity of numerous metabolic pathways and the contribution of nutrients to specific metabolite pools; however, SIRM experiments can be difficult to execute, and data interpretation is challenging. Furthermore, standardization of analytical procedures and workflows remain significant obstacles for widespread reproducibility. Here, we demonstrate the workflow of a typical SIRM experiment and suggest experimental controls and measures of cross-validation that improve data interpretation. Inhibitors of glycolysis and oxidative phosphorylation as well as mitochondrial uncouplers serve as pharmacological controls, which help define metabolic flux configurations that occur under well-controlled metabolic states. We demonstrate how such controls and time course labeling experiments improve confidence in metabolite assignments as well as delineate metabolic pathway relationships. Moreover, we demonstrate how radiolabeled tracers and extracellular flux analyses integrate with SIRM to improve data interpretation. Collectively, these results show how integration of flux methodologies and use of pharmacological controls increase confidence in SIRM data and provide new biological insights.

Metandem: An online software tool for mass spectrometry-based isobaric labeling metabolomics

Mass spectrometry-based stable isotope labeling provides the advantages of multiplexing capability and accurate quantification but requires tailored bioinformatics tools for data analysis. Despite the rapid advancements in analytical methodology, it is often challenging to analyze stable isotope labeling-based metabolomics data, particularly for isobaric labeling using MS/MS reporter ions for quantification. We report Metandem, a novel online software tool for isobaric labeling-based metabolomics, freely available at http://metandem.com/web/. Metandem provides a comprehensive data analysis pipeline integrating feature extraction, metabolite quantification, metabolite identification, batch processing of multiple data files, online parameter optimization for custom datasets, data normalization, and statistical analysis. Systematic evaluation of the Metandem tool was demonstrated on UPLC-MS/MS, nanoLC-MS/MS, CE-MS/MS and MALDI-MS platforms, via duplex, 4-plex, 10-plex, and 12-plex isobaric labeling experiments and the application to various biological samples.

Systems-level analysis of isotopic labeling in untargeted metabolomic data by X13CMS

Identification of previously unreported metabolites (so-called 'unknowns') in untargeted metabolomic data has become an increasingly active area of research. Considerably less attention, however, has been dedicated to identifying unknown metabolic pathways. Yet, for each unknown metabolite structure, there is potentially a yet-to-be-discovered chemical transformation. Elucidating these biochemical connections is essential to advancing our knowledge of cellular metabolism and can be achieved by tracking an isotopically labeled precursor to an unexpected product. In addition to their role in mapping metabolic fates, isotopic labels also provide critical insight into pathway dynamics (i.e., metabolic fluxes) that cannot be obtained from conventional label-free metabolomic analyses. When labeling is compared quantitatively between conditions, for example, isotopic tracers can enable relative pathway activities to be inferred. To discover unexpected chemical transformations or unanticipated differences in metabolic pathway activities, we have developed X13CMS, a platform for analyzing liquid chromatography/mass spectrometry (LC/MS) data at the systems level. After providing cells, animals, or patients with an isotopically enriched metabolite (e.g., 13C, 15N, or 2H), X13CMS identifies compounds that have incorporated the isotopic tracer and reports the extent of labeling for each. The analysis can be performed with a single condition, or isotopic fates can be compared between multiple conditions. The choice of which metabolite to enrich and which isotopic label to use is highly context dependent, but 13C-glucose and 13C-glutamine are often applied because they feed a large number of metabolic pathways. X13CMS is freely available.

Mapping the metabolism of five amino acids in bloodstream form Trypanosoma brucei using U-13C-labelled substrates and LC-MS

The metabolism of the parasite Trypanosoma brucei has been the focus of numerous studies since the 1940s. Recently it was shown, using metabolomics coupled with heavy-atom isotope labelled glucose, that the metabolism of the bloodstream form parasite is more complex than previously thought. The present study also raised a number of questions regarding the origin of several metabolites, for example succinate, only a proportion of which derives from glucose. In order to answer some of these questions and explore the metabolism of bloodstream form T. brucei in more depth we followed the fate of five heavy labelled amino acids – glutamine, proline, methionine, cysteine and arginine – using an LC–MS based metabolomics approach. We found that some of these amino acids have roles beyond those previously thought and we have tentatively identified some unexpected metabolites which need to be confirmed and their function determined.

Peak Annotation and Verification Engine for Untargeted LC-MS Metabolomics

Untargeted metabolomics can detect more than 10 000 peaks in a single LC-MS run. The correspondence between these peaks and metabolites, however, remains unclear. Here, we introduce a Peak Annotation and Verification Engine (PAVE) for annotating untargeted microbial metabolomics data. The workflow involves growing cells in 13C and 15N isotope-labeled media to identify peaks from biological compounds and their carbon and nitrogen atom counts. Improved deisotoping and deadducting are enabled by algorithms that integrate positive mode, negative mode, and labeling data. To distinguish metabolites and their fragments, PAVE experimentally measures the response of each peak to weak in-source collision induced dissociation, which increases the peak intensity for fragments while decreasing it for their parent ions. The molecular formulas of the putative metabolites are then assigned based on database searching using both m/ z and C/N atom counts. Application of this procedure to Saccharomyces cerevisiae and Escherichia coli revealed that more than 80% of peaks do not label, i.e., are environmental contaminants. More than 70% of the biological peaks are isotopic variants, adducts, fragments, or mass spectrometry artifacts yielding ∼2000 apparent metabolites across the two organisms. About 650 match to a known metabolite formula based on m/ z and C/N atom counts, with 220 assigned structures based on MS/MS and/or retention time to match to authenticated standards. Thus, PAVE enables systematic annotation of LC-MS metabolomics data with only ∼4% of peaks annotated as apparent metabolites.

Application of Stable Isotope Labels for Metabolomics in Studies in Fatty Liver Disease

The progression of nonalcoholic fatty liver disease (NAFLD) increases the risks of cirrhosis and cardiovascular disease. Marked alteration of both cytosolic and mitochondrial metabolism, and in combination with insulin resistance, increases hepatic glucose production. Utilization of stable isotope tracers to study liver metabolism offers deep insight into rearrangements of metabolic pathways and substrate-product relationships under the conditions leading to fatty liver and induced by diseases, drugs, toxins, or genetic manipulations. Isotope tracing untargeted metabolomics (ITUM) recently emerged as a powerful platform in which the label can be tracked in an untargeted fashion, revealing the penetration of substrates into metabolic pathways, even at low abundance. Here, we describe a protocol that can be utilized to study the changes in utilization of any labeled substrate toward a wide range of metabolites either in isolated liver cells or whole liver tissue under conditions mimicking various stages of fatty liver disease. Furthermore, a routine protocol for extraction, separation, and mass spectrometric detection of isotopically labeled metabolites in an untargeted or targeted fashion. An informatic approach to analyze stable isotope untargeted metabolomic datasets is also described.

Gluconeogenesis using glycerol as a substrate in bloodstream-form Trypanosoma brucei

Bloodstream form African trypanosomes are thought to rely exclusively upon glycolysis, using glucose as a substrate, for ATP production. Indeed, the pathway has long been considered a potential therapeutic target to tackle the devastating and neglected tropical diseases caused by these parasites. However, plasma membrane glucose and glycerol transporters are both expressed by trypanosomes and these parasites can infiltrate tissues that contain glycerol. Here, we show that bloodstream form trypanosomes can use glycerol for gluconeogenesis and for ATP production, particularly when deprived of glucose following hexose transporter depletion. We demonstrate that Trypanosoma brucei hexose transporters 1 and 2 (THT1 and THT2) are localized to the plasma membrane and that knockdown of THT1 expression leads to a growth defect that is more severe when THT2 is also knocked down. These data are consistent with THT1 and THT2 being the primary routes of glucose supply for the production of ATP by glycolysis. However, supplementation of the growth medium with glycerol substantially rescued the growth defect caused by THT1 and THT2 knockdown. Metabolomic analyses with heavy-isotope labelled glycerol demonstrated that trypanosomes take up glycerol and use it to synthesize intermediates of gluconeogenesis, including fructose 1,6-bisphosphate and hexose 6-phosphates, which feed the pentose phosphate pathway and variant surface glycoprotein biosynthesis. We used Cas9-mediated gene knockout to demonstrate a gluconeogenesis-specific, but fructose-1,6-bisphosphatase (Tb927.9.8720)-independent activity, converting fructose 1,6-bisphosphate into fructose 6-phosphate. In addition, we observed increased flux through the tricarboxylic acid cycle and the succinate shunt. Thus, contrary to prior thinking, gluconeogenesis can operate in bloodstream form T. brucei. This pathway, using glycerol as a physiological substrate, may be required in mammalian host tissues.

In Vivo Stable-Isotope Labeling and Mass-Spectrometry-Based Metabolic Profiling of a Potent Tobacco-Specific Carcinogen in Rats

The tobacco-specific nitrosamine, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), is a potent lung carcinogen that exerts its carcinogenic effects upon metabolic activation. The identification and quantitation of NNK metabolites could identify potential biomarkers of bioactivation and detoxification of this potent carcinogen and may be used to predict lung cancer susceptibility among smokers. Here, we used in vivo isotope-labeling and high-resolution-mass-spectrometry-based methods for the comprehensive profiling of all known and unknown NNK metabolites. The sample-enrichment, LC-MS, and data-analysis workflow, including a custom script for automated d0- d4- m/ z-pair-peak detection, enabled unbiased identification of numerous NNK metabolites. The structures of the metabolites were confirmed using targeted LC-MS2 with retention-time ( tR) and MS2-fragmentation comparisons to those of standards when possible. Eleven known metabolites and unchanged NNK were identified simultaneously. More importantly, our workflow revealed novel NNK metabolites, including 1,3-Diol (13), α-OH-methyl-NNAL-Gluc (14), nitro-NK- N-oxide (15), nitro-NAL- N-oxide (16), γ-OH NNAL (17), and three N-acetylcysteine (NAC) metabolites (18a-c). We measured the differences in the relative distributions of a panel of nitroso-containing NNK-specific metabolites in rats before and after phenobarbital (PB) treatment, and this served as a demonstration of a general strategy for the detection of metabolic differences in animal and cell systems. Lastly, we generated a d4-labeled NNK-metabolite mixture to be used as internal standards ( d4-rat urine) for the relative quantitation of NNK metabolites in humans, and this new strategy will be used to assess carcinogen exposure and ultimately to evaluate lung-cancer risk and susceptibility in smokers.

Nontargeted Identification of Tracer Incorporation in High-Resolution Mass Spectrometry

"Fluxomics" refers to the systematic analysis of metabolic fluxes in a biological system and may uncover novel dynamic properties of metabolism that remain undetected in conventional metabolomic approaches. In labeling experiments, tracer molecules are used to track changes in the isotopologue distribution of metabolites, which allows one to estimate fluxes in the metabolic network. Because unidentified compounds cannot be mapped on pathways, they are often neglected in labeling experiments. However, using recent developments in de novo annotation may allow to harvest the information present in these compounds if they can be identified. Here, we present a novel tool (HiResTEC) to detect tracer incorporation in high-resolution mass spectrometry data sets. The software automatically extracts a comprehensive, nonredundant list of all compounds showing more than 1% tracer incorporation in a nontargeted fashion. We explain and show in an example data set how mass precision and other filter heuristics, calculated on the raw data, can efficiently be used to reduce redundancy and noninformative signals by 95%. Ultimately, this allows to quickly investigate any labeling experiment for a complete set of labeled compounds (here 149) with acceptable false positive rates. We further re-evaluate a published data set from liquid chromatography-electrospray ionization (LC-ESI) to demonstrate broad applicability of our tool and emphasize importance of quality control (QC) tests. HiResTEC is provided as a package in the open source software framework R and is freely available on CRAN.

Benzoxaborole treatment perturbs S-adenosyl-L-methionine metabolism in Trypanosoma brucei

The parasitic protozoan Trypanosoma brucei causes Human African Trypanosomiasis and Nagana in other mammals. These diseases present a major socio-economic burden to large areas of sub-Saharan Africa. Current therapies involve complex and toxic regimens, which can lead to fatal side-effects. In addition, there is emerging evidence for drug resistance. AN5568 (SCYX-7158) is a novel benzoxaborole class compound that has been selected as a lead compound for the treatment of HAT, and has demonstrated effective clearance of both early and late stage trypanosomiasis in vivo. The compound is currently awaiting phase III clinical trials and could lead to a novel oral therapeutic for the treatment of HAT. However, the mode of action of AN5568 in T. brucei is unknown. This study aimed to investigate the mode of action of AN5568 against T. brucei, using a combination of molecular and metabolomics-based approaches.Treatment of blood-stage trypanosomes with AN5568 led to significant perturbations in parasite metabolism. In particular, elevated levels of metabolites involved in the metabolism of S-adenosyl-L-methionine, an essential methyl group donor, were found. Further comparative metabolomic analyses using an S-adenosyl-L-methionine-dependent methyltransferase inhibitor, sinefungin, showed the presence of several striking metabolic phenotypes common to both treatments. Furthermore, several metabolic changes in AN5568 treated parasites resemble those invoked in cells treated with a strong reducing agent, dithiothreitol, suggesting redox imbalances could be involved in the killing mechanism.

PHGDH Defines a Metabolic Subtype in Lung Adenocarcinomas with Poor Prognosis

Molecular signatures are emerging determinants of choice of therapy for lung adenocarcinomas. An evolving therapeutic approach includes targeting metabolic dependencies in cancers. Here, using an integrative approach, we have dissected the metabolic fingerprints of lung adenocarcinomas, and we show that Phosphoglycerate dehydrogenase (PHGDH), the rate-limiting enzyme in serine biosynthesis, is highly expressed in a adenocarcinoma subset with poor prognosis. This subset harbors a gene signature for DNA replication and proliferation. Accordingly, models with high levels of PHGDH display rapid proliferation, migration, and selective channeling of serine-derived carbons to glutathione and pyrimidines, while depletion of PHGDH shows potent and selective toxicity to this subset. Differential PHGDH protein levels were defined by its degradation, and the deubiquitinating enzyme JOSD2 is a regulator of its protein stability. Our study provides evidence that a unique metabolic program is activated in a lung adenocarcinoma subset, described by PHGDH, which confers growth and survival and may have therapeutic implications.

Deletion of transketolase triggers a stringent metabolic response in promastigotes and loss of virulence in amastigotes of Leishmania mexicana

Transketolase (TKT) is part of the non-oxidative branch of the pentose phosphate pathway (PPP). Here we describe the impact of removing this enzyme from the pathogenic protozoan Leishmania mexicana. Whereas the deletion had no obvious effect on cultured promastigote forms of the parasite, the Δtkt cells were not virulent in mice. Δtkt promastigotes were more susceptible to oxidative stress and various leishmanicidal drugs than wild-type, and metabolomics analysis revealed profound changes to metabolism in these cells. In addition to changes consistent with those directly related to the role of TKT in the PPP, central carbon metabolism was substantially decreased, the cells consumed significantly less glucose, flux through glycolysis diminished, and production of the main end products of metabolism was decreased. Only minor changes in RNA abundance from genes encoding enzymes in central carbon metabolism, however, were detected although fructose-1,6-bisphosphate aldolase activity was decreased two-fold in the knock-out cell line. We also showed that the dual localisation of TKT between cytosol and glycosomes is determined by the C-terminus of the enzyme and by engineering different variants of the enzyme we could alter its sub-cellular localisation. However, no effect on the overall flux of glucose was noted irrespective of whether the enzyme was found uniquely in either compartment, or in both.

Leishmania parasites endanger over 1 billion people worldwide, infecting 300,000 people and causing 20,000 deaths annually. In this study, we scrutinized metabolism in Leishmania mexicana after deletion of the gene encoding transketolase (TKT), an enzyme involved in sugar metabolism via the pentose phosphate pathway which plays key roles in creating ribose 5-phosphate for nucleotide synthesis and also defence against oxidative stress. The insect stage of the parasite, grown in culture medium, did not suffer from any obvious growth defect after the gene was deleted. However, its metabolism changed dramatically, with metabolomics indicating profound changes to flux through the pentose phosphate pathway: decreased glucose consumption, and generally enhanced efficiency in using metabolic substrates with reduced secretion of partially oxidised end products of metabolism. This ‘stringent’ metabolism is reminiscent of the mammalian stage parasites. The cells were also more sensitive to oxidative stress inducing agents and leishmanicidal drugs. Crucially, mice inoculated with the TKT knock-out parasites did not develop an infection pointing to the enzyme playing a key role in allowing the parasites to remain viable in the host, indicating that TKT may be considered a useful target for development of new drugs against leishmaniasis.

DeltaMS: a tool to track isotopologues in GC- and LC-MS data

INTRODUCTION

Stable isotopic labeling experiments are powerful tools to study metabolic pathways, to follow tracers and fluxes in biotic and abiotic transformations and to elucidate molecules involved in metal complexing.

OBJECTIVE

To introduce a software tool for the identification of isotopologues from mass spectrometry data.

METHODS

DeltaMS relies on XCMS peak detection and X¹³CMS isotopologue grouping and then analyses data for specific isotope ratios and the relative error of these ratios. It provides pipelines for recognition of isotope patterns in three experiment types commonly used in isotopic labeling studies: (1) search for isotope signatures with a specific mass shift and intensity ratio in one sample set, (2) analyze two sample sets for a specific mass shift and, optionally, the isotope ratio, whereby one sample set is isotope-labeled, and one is not, (3) analyze isotope-guided perturbation experiments with a setup described in X¹³CMS.

RESULTS

To illustrate the versatility of DeltaMS, we analyze data sets from case-studies that commonly pose challenges in evaluation of natural isotopes or isotopic signatures in labeling experiment. In these examples, the untargeted detection of sulfur, bromine and artificial metal isotopic patterns is enabled by the automated search for specific isotopes or isotope signatures.

CONCLUSION

DeltaMS provides a platform for the identification of (pre-defined) isotopologues in MS data from single samples or comparative metabolomics data sets.

Metabolomic profiling and stable isotope labelling of Trichomonas vaginalis and Tritrichomonas foetus reveal major differences in amino acid metabolism including the production of 2-hydroxyisocaproic acid, cystathionine and S-methylcysteine

Trichomonas vaginalis and Tritrichomonas foetus are pathogens that parasitise, respectively, human and bovine urogenital tracts causing disease. Using LC-MS, reference metabolomic profiles were obtained for both species and stable isotope labelling with D-[U-13C6] glucose was used to analyse central carbon metabolism. This facilitated a comparison of the metabolic pathways of T. vaginalis and T. foetus, extending earlier targeted biochemical studies. 43 metabolites, whose identities were confirmed by comparison of their retention times with authentic standards, occurred at more than 3-fold difference in peak intensity between T. vaginalis and T. foetus. 18 metabolites that were removed from or released into the medium during growth also showed more than 3-fold difference between the species. Major differences were observed in cysteine and methionine metabolism in which homocysteine, produced as a bi-product of trans-methylation, is catabolised by methionine γ-lyase in T. vaginalis but converted to cystathionine in T. foetus. Both species synthesise methylthioadenosine by an unusual mechanism, but it is not used as a substrate for methionine recycling. T. vaginalis also produces and exports high levels of S-methylcysteine, whereas only negligible levels were found in T. foetus which maintains significantly higher intracellular levels of cysteine. 13C-labeling confirmed that both cysteine and S-methylcysteine are synthesised by T. vaginalis; S-methylcysteine can be generated by recombinant T. vaginalis cysteine synthase using phosphoserine and methanethiol. T. foetus contained higher levels of ornithine and citrulline than T. vaginalis and exported increased levels of putrescine, suggesting greater flux through the arginine dihydrolase pathway. T. vaginalis produced and exported hydroxy acid derivatives of certain amino acids, particularly 2-hydroxyisocaproic acid derived from leucine, whereas negligible levels of these metabolites occurred in T. foetus.

The fate of lysine: Non-targeted stable isotope analysis reveals parallel ways for lysine catabolization in Phaeobacter inhibens

For a detailed investigation of the degradation of lysine in Phaeobacter inhibens DSM 17395, stable isotope experiments with uniformly ¹³C labeled L-lysine were carried out with lysine adapted cells and the metabolites were analyzed using GC/MS and HPLC/MS. A non-targeted stable isotope analysis was used which compares labeled and not labeled samples to determine the Mass Isotopomer Distribution not only for known metabolites but for all labeled compounds in our GC/MS analysis. We show that P. inhibens uses at least two parallel pathways for the first degradation steps of lysine. Further investigations identified L-pipecolate as an L-lysine degradation intermediate in P. inhibens. The analysis of HPLC/MS data as well as the labeling data of tricarboxylic acid (TCA) cycle intermediates show that L-lysine is not only catabolized directly to acetyl-CoA but also via the ethylmalonyl-CoA-pathway, leading to entry points into the TCA cycle via acetyl-CoA, succinyl-CoA, and malate. Altogether the presented data give a detailed insight into the catabolization of L-lysine following the fate of ¹³C labeled carbon via several ways into the TCA cycle.