Neuronal metabolomics by ion mobility mass spectrometry: cocaine effects on glucose and selected biogenic amine metabolites in the frontal cortex, striatum, and thalamus of the rat

Metabolomic Profile Modification in the Cerebellum of Mice Repeatedly Exposed to Khat and Treated with β-Lactamase Inhibitor, Clavulanic Acid

BACKGROUND/OBJECTIVES

Catha edulis, commonly known as khat, is used for its psychoactive effects and is considered a natural amphetamine. The current study investigated the metabolomic profile in the cerebellum of mice after repeated exposure to khat and evaluated the effects of clavulanic acid on the metabolomic profile in the cerebellum in khat-treated mice.

METHODS

Male C67BL/6 mice that were 6-9 weeks old were recruited and divided into three groups: the control group was treated with 0.9% normal saline for 17 days; the khat group was given khat extract at a dose of 360 mg/kg via the intraperitoneal (i.p) route for 17 days; and another khat group was treated with khat for 17 days and clavulanic acid at a dose of 5 mg/kg for the last 7 days (days 11-17). At the end of the 17th day, the animals were sacrificed, and their brains were immediately collected and stored at -80 °C. The cerebellum region of the brain was isolated in each group by micropuncture using cryostat and underwent a metabolomics study via Gas Chromatography/Mass Spectroscopy (GC/MS). The total peak area ratios of the selected metabolites in the cerebellum after repeated exposure to the khat extract were significantly reduced (p < 0.05) and treatment of the khat group with clavulanic acid significantly increased (all p < 0.05) the total peak areas ratios of the selected metabolites when compared to their corresponding areas in the alternative khat group. These levels of selected metabolites were further confirmed by observing the metabolite peak area ratios and performing a heat map analysis and a principal compartment analysis of the samples in the cerebellum.

RESULTS

A network analysis of altered metabolites in the cerebellum showed a strong correlation between the different metabolites, which showed that an increase in one metabolite can modulate the levels of others. An analysis using the MetaboAnalyst software revealed the involvement of selected altered metabolites like lactic acid in many signaling pathways, like gluconeogenesis, while enrichment analysis data showed altered pathways for pyruvate metabolism and disease pathogenesis. Finally, a network analysis showed that selected metabolites were linked with other metabolites, indicating drug-drug interactions.

CONCLUSIONS

The present study showed that repeated exposure of mice to khat altered the levels of various metabolites in the cerebellum which are involved in the pathogenesis of different diseases, signaling pathways, and interactions with the pharmacokinetic profile of other therapeutic drugs. The treatment of khat-treated mice with clavulanic acid positively modified the metabolomics profile in the cerebellum and increased the levels of the altered metabolites.

Neuroinflammation and Neurometabolomic Profiling in Fentanyl Overdose Mouse Model Treated with Novel β-Lactam, MC-100093, and Ceftriaxone

Opioid-related deaths are attributed to overdoses, and fentanyl overdose has been on the rise in many parts of the world, including the USA. Glutamate transporter 1 (GLT-1) has been identified as a therapeutic target in several preclinical models of substance use disorders, and β-lactams effectively enhance its expression and function. In the current study, we characterized the metabolomic profile of the nucleus accumbens (NAc) in fentanyl-overdose mouse models, and we evaluated the protective effects of the functional enhancement of GLT-1 using β-lactams, ceftriaxone, and MC-100093. BALB/c mice were divided into four groups: control, fentanyl, fentanyl/ceftriaxone, and fentanyl/MC-100093. While the control group was intraperitoneally (i.p.) injected with normal saline simultaneously with other groups, all fentanyl groups were i.p. injected with 1 mg/kg of fentanyl as an overdose after habituation with four repetitive non-consecutive moderate doses (0.05 mg/kg) of fentanyl for a period of seven days. MC-100093 (50 mg/kg) and ceftriaxone (200 mg/kg) were i.p. injected from days 5 to 9. Gas chromatography-mass spectrometry (GC-MS) was used for metabolomics, and Western blotting was performed to determine the expression of target proteins. Y-maze spontaneous alternation performance and the open field activity monitoring system were used to measure behavioral manifestations. Fentanyl overdose altered the abundance of about 30 metabolites, reduced the expression of GLT-1, and induced the expression of inflammatory mediators IL-6 and TLR-4 in the NAc. MC-100093 and ceftriaxone attenuated the effects of fentanyl-induced downregulation of GLT-1 and upregulation of IL-6; however, only ceftriaxone attenuated fentanyl-induced upregulation of TRL4 expression. Both of the β-lactams attenuated the effects of fentanyl overdose on locomotor activities but did not induce significant changes in the overall metabolomic profile. Our findings revealed that the exposure to a high dose of fentanyl causes alterations in key metabolic pathways in the NAc. Pretreatment with ceftriaxone and MC-100093 normalized fentanyl-induced downregulation of GLT-1 expression with subsequent attenuation of neuroinflammation as well as the hyperactivity, indicating that β-lactams may be promising drugs for treating fentanyl use disorder.

Right in two: capabilities of ion mobility spectrometry for untargeted metabolomics

This mini review focuses on the opportunities provided by current and emerging separation techniques for mass spectrometry metabolomics. The purpose of separation technologies in metabolomics is primarily to reduce complexity of the heterogeneous systems studied, and to provide concentration enrichment by increasing sensitivity towards the quantification of low abundance metabolites. For this reason, a wide variety of separation systems, from column chemistries to solvent compositions and multidimensional separations, have been applied in the field. Multidimensional separations are a common method in both proteomics applications and gas chromatography mass spectrometry, allowing orthogonal separations to further reduce analytical complexity and expand peak capacity. These applications contribute to exponential increases in run times concomitant with first dimension fractionation followed by second dimension separations. Multidimensional liquid chromatography to increase peak capacity in metabolomics, when compared to the potential of running additional samples or replicates and increasing statistical confidence, mean that uptake of these methods has been minimal. In contrast, in the last 15 years there have been significant advances in the resolution and sensitivity of ion mobility spectrometry, to the point where high-resolution separation of analytes based on their collision cross section approaches chromatographic separation, with minimal loss in sensitivity. Additionally, ion mobility separations can be performed on a chromatographic timescale with little reduction in instrument duty cycle. In this review, we compare ion mobility separation to liquid chromatographic separation, highlight the history of the use of ion mobility separations in metabolomics, outline the current state-of-the-art in the field, and discuss the future outlook of the technology. "Where there is one, you're bound to divide it. Right in two", James Maynard Keenan.

Evaluation of Cocaine Effect on Endogenous Metabolites of HepG2 Cells Using Targeted Metabolomics

Cocaine toxicity has been a subject of study because cocaine is one of the most common and potent drugs of abuse. In the current study the effect of cocaine on human liver cancer cell line (HepG2) was assessed. Cocaine toxicity (IC50) on HepG2 cells was experimentally calculated using an XTT assay at 2.428 mM. The metabolic profile of HepG2 cells was further evaluated to investigate the cytotoxic activity of cocaine at 2 mM at three different time points. Cell medium and intracellular material samples were analyzed with a validated HILIC-MS/MS method for targeted metabolomics on an ACQUITY Amide column in gradient mode with detection on a triple quadrupole mass spectrometer in multiple reaction monitoring. About 106 hydrophilic metabolites from different metabolic pathways were monitored. Multivariate analysis clearly separated the studied groups (cocaine-treated and control samples) and revealed potential biomarkers in the extracellular and intracellular samples. A predominant effect of cocaine administration on alanine, aspartate, and glutamate metabolic pathway was observed. Moreover, taurine and hypotaurine metabolism were found to be affected in cocaine-treated cells. Targeted metabolomics managed to reveal metabolic changes upon cocaine administration, however deciphering the exact cocaine cytotoxic mechanism is still challenging.

Plasma metabolites changes in male heroin addicts during acute and protracted withdrawal

BACKGROUND

Heroin addiction and withdrawal have been associated with an increased risk for infectious diseases and psychological complications. However, the changes of metabolites in heroin addicts during withdrawal remain largely unknown.

METHODS

A total of 50 participants including 20 heroin addicts with acute abstinence stage, 15 with protracted abstinence stage and 15 healthy controls, were recruited. We performed metabolic profiling of plasma samples based on ultraperformance liquid chromatography coupled to tandem mass spectrometry to explore the potential biomarkers and mechanisms of heroin withdrawal.

RESULTS

Among the metabolites analyzed, omega-6 polyunsaturated fatty acids (linoleic acid, dihomo-gamma-linolenic acid, arachidonic acid, n-6 docosapentaenoic acid), omega-3 polyunsaturated fatty acids (docosahexaenoic acid, docosapentaenoic acid), aromatic amino acids (phenylalanine, tyrosine, tryptophan), and intermediates of the tricarboxylic acid cycle (oxoglutaric acid, isocitric acid) were significantly reduced during acute heroin withdrawal. Although majority of the metabolite changes could recover after months of withdrawal, the levels of alpha-aminobutyric acid, alloisoleucine, ketoleucine, and oxalic acid do not recover.

CONCLUSIONS

In conclusion, the plasma metabolites undergo tremendous changes during heroin withdrawal. Through metabolomic analysis, we have identified links between a framework of metabolic perturbations and withdrawal stages in heroin addicts.

Metabolic phenotyping of opioid and psychostimulant addiction: A novel approach for biomarker discovery and biochemical understanding of the disorder

Despite the progress in characterising the pharmacological profile of drugs of abuse, their precise biochemical impact remains unclear. The metabolome reflects the multifaceted biochemical processes occurring within a biological system. This includes those encoded in the genome but also those arising from environmental/exogenous exposures and interactions between the two. Using metabolomics, the biochemical derangements associated with substance abuse can be determined as the individual transitions from recreational drug to chronic use (dependence). By understanding the biomolecular perturbations along this time course and how they vary across individuals, metabolomics can elucidate biochemical mechanisms of the addiction cycle (dependence/withdrawal/relapse) and predict prognosis (recovery/relapse). In this review, we summarise human and animal metabolomic studies in the field of opioid and psychostimulant addiction. We highlight the importance of metabolomics as a powerful approach for biomarker discovery and its potential to guide personalised pharmacotherapeutic strategies for addiction targeted towards the individual's metabolome.

Applications of Metabolomics in Forensic Toxicology and Forensic Medicine

Forensic toxicology and forensic medicine are unique among all other medical fields because of their essential legal impact, especially in civil and criminal cases. New high-throughput technologies, borrowed from chemistry and physics, have proven that metabolomics, the youngest of the “omics sciences”, could be one of the most powerful tools for monitoring changes in forensic disciplines. Metabolomics is a particular method that allows for the measurement of metabolic changes in a multicellular system using two different approaches: targeted and untargeted. Targeted studies are focused on a known number of defined metabolites. Untargeted metabolomics aims to capture all metabolites present in a sample. Different statistical approaches (e.g., uni- or multivariate statistics, machine learning) can be applied to extract useful and important information in both cases. This review aims to describe the role of metabolomics in forensic toxicology and in forensic medicine.

Metabolomics in Psychiatric Disorders: What We Learn from Animal Models

Biomarkers are a recent research target within biological factors of psychiatric disorders. There is growing evidence for deriving biomarkers within psychiatric disorders in serum or urine samples in humans, however, few studies have investigated this differentiation in brain or cerebral fluid samples in psychiatric disorders. As brain samples from humans are only available at autopsy, animal models are commonly applied to determine the pathogenesis of psychiatric diseases and to test treatment strategies. The aim of this review is to summarize studies on biomarkers in animal models for psychiatric disorders. For depression, anxiety and addiction disorders studies, biomarkers in animal brains are available. Furthermore, several studies have investigated psychiatric medication, e.g., antipsychotics, antidepressants, or mood stabilizers, in animals. The most notable changes in biomarkers in depressed animal models were related to the glutamate-γ-aminobutyric acid-glutamine-cycle. In anxiety models, alterations in amino acid and energy metabolism (i.e., mitochondrial regulation) were observed. Addicted animals showed several biomarkers according to the induced drugs. In summary, animal models provide some direct insights into the cellular metabolites that are produced during psychiatric processes. In addition, the influence on biomarkers due to short- or long-term medication is a noticeable finding. Further studies should combine representative animal models and human studies on cerebral fluid to improve insight into mental disorders and advance the development of novel treatment strategies.

Current Understanding of Methamphetamine-Associated Metabolic Changes Revealed by the Metabolomics Approach

Metabolomics is a powerful tool used in the description of metabolic system perturbations caused by diseases or abnormal conditions, and it usually involves qualitative and/or quantitative metabolome determination, accompanied by bioinformatics assessment. Methamphetamine is a psychostimulant with serious abuse potential and due to the absence of effective pharmacotherapy and a high recurrence potential, methamphetamine addiction is a grave issue. Moreover, its addiction mechanisms remain unclear, probably due to the lack of experimental models that reflect personal genetic variances and environmental factors determining drug addiction occurrence. The metabolic approach is only recently being used to study the metabolic effects induced by a variety of methamphetamine exposure statuses, in order to investigate metabolic disturbances related to the adverse effects and discover potential methamphetamine addiction biomarkers. To provide a critical overview of methamphetamine-associated metabolic changes revealed in recent years using the metabolomics approach, we discussed methamphetamine toxicity, applications of metabolomics in drug abuse and addiction studies, biological samples used in metabolomics, and previous studies on metabolic alterations in a variety of biological samples—including the brain, hair, serum, plasma, and urine—following methamphetamine exposure in animal studies. Metabolic alterations observed in animal brain and other biological samples after methamphetamine exposure were associated with neuronal and energy metabolism disruptions. This review highlights the significance of further metabolomics studies in the area of methamphetamine addiction research. These findings will contribute to a better understanding of metabolic changes induced by methamphetamine addiction progress and to the design of further studies targeting the discovery of methamphetamine addiction biomarkers and therapeutic targets.

Analysis of neurotransmitter levels in addiction-related brain regions during synthetic cathinone self-administration in male Sprague-Dawley rats

RATIONALE

Synthetic cathinones are used as stimulants of abuse. Different stimulants may induce distinct rates of disease progression, yielding neurochemical changes that may vary across brain regions or neurotransmitter systems.

OBJECTIVES

This research sought to behaviorally and chemically differentiate stages of synthetic cathinone abuse through rodent self-administration and measurement of the neurotransmitter profile in multiple brain regions.

METHODS

Male rats were trained to self-administer α-PVP, mephedrone (4MMC), or saline. Half of each drug group stopped self-administering after autoshaping; the other half self-administered for another 21 days. Brain tissue from amygdala, hippocampus, hypothalamus, PFC, striatum, and thalamus was profiled with electrochemical detection to assess neurotransmitter levels.

RESULTS

During autoshaping, the majority of infusions were delivered noncontingently. In the self-administration phase, rats responded more for α-PVP and 4MMC than for saline, demonstrating that both synthetic cathinones were reinforcing. Longer durations of exposure elevated 5-HIAA in hypothalamus, PFC, and hippocampus, indicating that learning may produce changes in addiction-related brain regions. Both synthetic cathinones decreased norepinephrine in hippocampus, while α-PVP decreased glutamate in hippocampus and PFC, and 4MMC decreased glutamate in thalamus. Furthermore, α-PVP increased dopaminergic metabolites in striatum, whereas 4MMC decreased serotonin in the amygdala, hippocampus, and PFC. Interestingly, neither synthetic cathinone affected dopamine levels despite their functional effects on the dopaminergic system.

CONCLUSIONS

In summary, the neurotransmitter changes observed here suggest that synthetic cathinone use likely produces sequential neurochemical changes during the transition from use to abuse. Consequently, treatment need may differ depending on the progression of synthetic cathinone abuse.

Analytical considerations for (un)-targeted metabolomic studies with special focus on forensic applications

Over the past few years, the interest in metabolomics has increased in various fields including forensic toxicology. Forensic analysis typically requires a high degree of accuracy, which is often a problem in metabolomics applications. We aimed for a systematic evaluation of different analytical considerations of a metabolomics workflow allowing a targeted approach within an untargeted setup. Samples with 69 metabolites from different chemical classes were qualitatively and quantitatively analyzed on a high resolution quadrupole time of flight mass spectrometer coupled to liquid chromatography (UHPLC-QTOF). Three issues were addressed: (a) Two different approaches on "blind matrix" a simulated body fluid (SBF) and plasma-filtrate, were tested for calibration samples; (b) comparison of two different HPLC columns, reverse-phase (RP) and hydrophilic interaction chromatography (HILIC); and (c) comparison of three different acquisition modes (TOF-MS, information dependent data acquisition (IDA), and sequential window acquisition of all theoretical fragment-ion spectra (SWATH). Samples were measured repeatedly for method comparison based on sensitivity, accuracy, precision, and detection robustness. The blind matrices showed similar accuracy for most analytes, while SBF provided an easier preparation with satisfying results. To cover a wide part of the human metabolome, a combination of RP and HILIC showed the best results. The different scan modes performed equally regarding metabolite quantification while TOF-MS was more sensitive but lacked MS/MS spectra generation. IDA and SWATH files were aligned to various databases where IDA showed good MS/MS spectra matches. SWATH seemed to be beneficial in detection rate but was incompatible with many important software tools in metabolomics.

Using Metabolomics to Investigate Biomarkers of Drug Addiction

Drug addiction has been associated with an increased risk for cancer, psychological complications, heart, liver, and lung disease, as well as infection. While genes have been identified that can mark individuals at risk for substance abuse, the initiation step of addiction is attributed to persistent metabolic disruptions occurring following the first instance of narcotic drug use. Advances in analytical technologies can enable the detection of thousands of signals in body fluids and excreta that can be used to define biochemical profiles of addiction. Today, these approaches hold promise for determining how exposure to drugs, in the absence or presence of other environmentally relevant factors, can impact human metabolism. We posit that these can lead to candidate biomarkers of drug dependence, treatment, withdrawal, or relapse.

Performance of a High-Pressure Liquid Chromatography-Ion Mobility-Mass Spectrometry System for Metabolic Profiling

A commercial liquid chromatography/drift tube ion mobility-mass spectrometer (LC/IM-MS) was evaluated for its utility in global metabolomics analysis. Performance was assessed using 12 targeted metabolite standards where the limit of detection (LOD), linear dynamic range, resolving power, and collision cross section (Ω) are reported for each standard. Data were collected in three different instrument operation modes: flow injection analysis with IM-MS (FIA/IM-MS), LC/MS, and LC/IM-MS. Metabolomics analyses of human plasma and HaCaT cells were used to compare the above three operation modes. LC/MS provides linearity in response, data processing automation, improved limits of detection, and ease of use. Advantages of LC/IM-MS and FIA/IM-MS include the ability to develop mobility-mass trend lines for structurally similar biomolecules, increased peak capacity, reduction of chemical/matrix noise, improvement in signal-to-noise, and separations of isobar/isomer compounds that are not resolved by LC. We further tested the feasibility of incorporating IM-MS into conventional LC/MS metabolomics workflows. In general, the addition of ion mobility dimension has increased the separation of compounds in complex biological matrixes and has the potential to largely improve the throughput of metabolomics analysis.

Investigation on the combined effect of cocaine and ethanol administration through a liquid chromatography-mass spectrometry metabolomics approach

Alcohol is the most widely consumed legal drug, whereas cocaine is the illicit psychostimulant most commonly used in Europe. The combined use of alcohol and cocaine is frequent among drug-abuse consumers and leads to further exacerbation of health consequences compared to individual consumption. The pharmacokinetic and metabolic interactions leading to an increase in their combined toxicity still remains poorly understood. Here, the first metabolomics study of combined cocaine and ethanol chronic exposure effects is reported. A Liquid Chromatography strategy based on sample derivatization with 9-fluorenylmethyloxycarbonyl chloride and using a C18 column coupled to high resolution Mass Spectrometry (time of flight analyzer) was employed to analyze plasma from rats exposed intravenously to these drugs in a 52-min analysis. Using a combination of non-supervised and supervised multivariate analysis the metabolic differences between our experimental groups were explored and unraveled. A comparative analysis of the individual models and their variable importance in the projection values have shown that every experiment intervention includes a subset of specific metabolites. Eleven of these metabolites were annotated, where eight were unequivocally identified using standards and three were tentatively identified by matching the MS/MS spectra to libraries. The results demonstrated that the affected metabolic pathways were mainly those related to the metabolism of different amino acids.

Application of ion mobility tandem mass spectrometry to compositional and structural analysis of glycopeptides extracted from the urine of a patient diagnosed with Schindler disease

RATIONALE

Schindler disease is caused by the deficient activity of α-N-acetylgalactosaminidase, which leads to an abnormal accumulation of O-glycopeptides in tissues and body fluids. In this work the Schindler condition is for the first time approached by ion mobility (IMS) tandem mass spectrometry (MS/MS), for determining urine glycopeptide fingerprints and discriminate isomeric structures.

METHODS

IMS-MS experiments were conducted on a Synapt G2s mass spectrometer operating in negative ion mode. A glycopeptide mixture extracted from the urine of a patient suffering from Schindler disease was dissolved in methanol and infused into the mass spectrometer by electrospray ionization using a syringe-pump system. MS/MS was performed by collision-induced dissociation (CID) at low energies, after mobility separation in the transfer cell. Data acquisition and processing were performed using MassLynx and Waters Driftscope software.

RESULTS

IMS-MS data indicated that the attachment of one or two amino acids to the carbohydrate backbone has a minimal influence on the molecule conformation, which limits the discrimination of the free oligosaccharides from the glycosylated amino acids and dipeptides. The structural analysis by CID MS/MS in combination with IMS-MS of species exhibiting the same m/z but different configurations demonstrated for the first time the presence of positional isomers for some of the Schindler disease biomarker candidates.

CONCLUSIONS

The IMS-MS and CID MS/MS platform was for the first time optimized and applied to Schindler disease glycourinome. By this approach the separation and characterization of Neu5Ac positional isomers was possible. IMS CID MS/MS showed the ability to determine the type of the glycopeptide isomers from a series of possible candidates.

Application of metabolomics to toxicology of drugs of abuse: A mini review of metabolomics approach to acute and chronic toxicity studies

Metabolomics has been widely applied to toxicological fields, especially to elucidate the mechanism of action of toxicity. In this review, metabolomics application with focus on the studies of chronic and acute toxicities of drugs of abuse like stimulants, opioids and the recently-distributed designer drugs will be presented in addition to an outline of basic analytical techniques used in metabolomics. Limitation of metabolomics studies and future perspectives will be also provided.

Highly sensitive isotope-dilution liquid-chromatography-electrospray ionization-tandem-mass spectrometry approach to study the drug-mediated modulation of dopamine and serotonin levels in Caenorhabditis elegans

Dopamine (DA) and serotonin (SRT) are monoamine neurotransmitters that play a key role in regulating the central and peripheral nervous system. Their impaired metabolism has been implicated in several neurological disorders, such as Parkinson's disease and depression. Consequently, it is imperative to monitor changes in levels of these low-abundant neurotransmitters and their role in mediating disease. For the first time, a rapid, specific and sensitive isotope-dilution liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed and validated for the quantification of DA and SRT in the nematode Caenorhabditis elegans (C. elegans). This model organism offers a unique approach for studying the effect of various drugs and environmental conditions on neurotransmitter levels, given by the conserved DA and SRT biology, including synaptic release, trafficking and formation. We introduce a novel sample preparation protocol incorporating the usage of sodium thiosulfate in perchloric acid as extraction medium that assures high recovery of the relatively unstable neurotransmitters monitored. Moreover, the use of both deuterated internal standards and the multiple reaction monitoring (MRM) technique allows for unequivocal quantification. Thereby, to the best of our knowledge, we achieve a detection sensitivity that clearly exceeds those of published DA and SRT quantification methods in various matrices. We are the first to show that exposure of C. elegans to the monoamine oxidase B (MAO-B) inhibitor selegiline or the catechol-O-methyltransferase (COMT) inhibitor tolcapone, in order to block DA and SRT degradation, resulted in accumulation of the respective neurotransmitter. Assessment of a behavioral output of the dopaminergic system (basal slowing response) corroborated the analytical LC-MS/MS data. Thus, utilization of the C. elegans model system in conjunction with our analytical method is well-suited to investigate drug-mediated modulation of the DA and SRT system in order to identify compounds with neuroprotective or regenerative properties.

Omics-Based Biomarkers: Application of Metabolomics in Neuropsychiatric Disorders

One of the major concerns of modern society is to identify putative biomarkers that serve as a valuable early diagnostic tool to identify a subset of patients with increased risk to develop neuropsychiatric disorders. Biomarker identification in neuropsychiatric disorders is proposed to offer a number of important benefits to patient well-being, including prediction of forthcoming disease, diagnostic precision, and a level of disease description that would guide treatment choice. Nowadays, the metabolomics approach has unlocked new possibilities in diagnostics of devastating disorders like neuropsychiatric disorders. Metabolomics-based technologies have the potential to map early biochemical changes in disease and hence provide an opportunity to develop predictive biomarkers that can be used as indicators of pathological abnormalities prior to development of clinical symptoms of neuropsychiatric disorders. This review highlights different -omics strategies for biomarker discovery in neuropsychiatric disorders. We also highlight initial outcomes from metabolomics studies in psychiatric disorders such as schizophrenia, bipolar disorder, and addictive disorders. This review will also present issues and challenges regarding the implementation of the metabolomics approach as a routine diagnostic tool in the clinical laboratory in context with neuropsychiatric disorders.

Structural mass spectrometry of tissue extracts to distinguish cancerous and non-cancerous breast diseases

Aberrant metabolism in breast cancer tumors has been widely studied by both targeted and untargeted analyses to characterize the affected metabolic pathways. In this work, we utilize ultra-performance liquid chromatography (UPLC) in tandem with ion mobility-mass spectrometry (IM-MS), which provides chromatographic, structural, and mass information, to characterize the aberrant metabolism associated with breast diseases such as cancer. In a double-blind analysis of matched control (n = 3) and disease tissues (n = 3), samples were homogenized, polar metabolites were extracted, and the extracts were characterized by UPLC-IM-MS/MS. Principle component analysis revealed a strong separation between disease tissues, with one diseased tissue clustering with the control tissues along PC1 and two others separated along PC2. Using post-ion mobility MS/MS spectra acquired by data-independent acquisition, the features giving rise to the observed grouping were determined to be biomolecules associated with aggressive breast cancer tumors, including glutathione, oxidized glutathione, thymosins β4 and β10, and choline-containing species. Pathology reports revealed the outlier of the disease tissues to be a benign fibroadenoma, whereas the other disease tissues represented highly metabolic benign and aggressive tumors. This IM-MS-based workflow bridges the transition from untargeted metabolomic profiling to tentative identifications of key descriptive molecular features using data acquired in one analysis, with additional experiments performed only for validation. The ability to resolve cancerous and non-cancerous tissues at the biomolecular level demonstrates UPLC-IM-MS/MS as a robust and sensitive platform for metabolomic profiling of tissues.

Rapid profiling and identification of anthocyanins in fruits with Hadamard transform ion mobility mass spectrometry

The use of Hadamard transform ion mobility mass spectrometry (HT-IMMS) in the profiling of anthocyanins from different fruits is presented. Samples extracted with acidic methanol and purified with solid phase extraction were analyzed with direct IMMS infusion. The separation of various anthocyanins was achieved within 30s with resolving powers up to 110. The ion mobility drift times correlated with their mass-to-charge ratios with a correlation coefficient of 0.979 to produce a trend line that was characteristic for anthocyanins. Isomers with the same anthocyanidin but different hexoses were differentiated by ion mobility spectrometry. Furthermore, mobility separated ions underwent collision induced dissociation at the IMMS interface to provide MS/MS spectra. These fragmentation spectra aided in the identification of anthocyanidins via the loss of the saccharide groups. IMMS appears to be a rapid and efficient approach for profiling and identifying anthocyanins.

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.

A nano ultra-performance liquid chromatography-high resolution mass spectrometry approach for global metabolomic profiling and case study on drug-resistant multiple myeloma

Global metabolomics relies on highly reproducible and sensitive detection of a wide range of metabolites in biological samples. Here we report the optimization of metabolome analysis by nanoflow ultraperformance liquid chromatography coupled to high-resolution orbitrap mass spectrometry. Reliable peak features were extracted from the LC-MS runs based on mandatory detection in duplicates and additional noise filtering according to blank injections. The run-to-run variation in peak area showed a median of 14%, and the false discovery rate during a mock comparison was evaluated. To maximize the number of peak features identified, we systematically characterized the effect of sample loading amount, gradient length, and MS resolution. The number of features initially rose and later reached a plateau as a function of sample amount, fitting a hyperbolic curve. Longer gradients improved unique feature detection in part by time-resolving isobaric species. Increasing the MS resolution up to 120000 also aided in the differentiation of near isobaric metabolites, but higher MS resolution reduced the data acquisition rate and conferred no benefits, as predicted from a theoretical simulation of possible metabolites. Moreover, a biphasic LC gradient allowed even distribution of peak features across the elution, yielding markedly more peak features than the linear gradient. Using this robust nUPLC-HRMS platform, we were able to consistently analyze ~6500 metabolite features in a single 60 min gradient from 2 mg of yeast, equivalent to ~50 million cells. We applied this optimized method in a case study of drug (bortezomib) resistant and drug-sensitive multiple myeloma cells. Overall, 18% of metabolite features were matched to KEGG identifiers, enabling pathway enrichment analysis. Principal component analysis and heat map data correctly clustered isogenic phenotypes, highlighting the potential for hundreds of small molecule biomarkers of cancer drug resistance.

Electrospray Quadrupole Travelling Wave Ion Mobility Time-of-Flight Mass Spectrometry for the Detection of Plasma Metabolome Changes Caused by Xanthohumol in Obese Zucker (fa/fa) Rats

This study reports on the use of traveling wave ion mobility quadrupole time-of-flight (ToF) mass spectrometry for plasma metabolomics. Plasma metabolite profiles of obese Zucker fa/fa rats were obtained after the administration of different oral doses of Xanthohumol; a hop-derived dietary supplement. Liquid chromatography coupled data independent tandem mass spectrometry (LC-MSE) and LC-ion mobility spectrometry (IMS)-MSE acquisitions were conducted in both positive and negative modes using a Synapt G2 High Definition Mass Spectrometry (HDMS) instrument. This method provides identification of metabolite classes in rat plasma using parallel alternating low energy and high energy collision spectral acquisition modes. Data sets were analyzed using pattern recognition methods. Statistically significant (p < 0.05 and fold change (FC) threshold > 1.5) features were selected to identify the up-/down-regulated metabolite classes. Ion mobility data visualized using drift scope software provided a graphical read-out of differences in metabolite classes.