Metabolomics applications of FT-ICR mass spectrometry

Double-Helix Electrode Ion Funnel: A New Ion Funnel Design with an Extended Mass Range

The development of an atmospheric pressure interface (API) with a high ion transfer efficiency and wide mass range is advantageous for the performance improvement of mass spectrometry (MS) instruments. In this work, a novel ion guide, namely, the double-helix electrode ion funnel (DHE-IF), has been developed to enhance the ion transmission over a wide mass range in the rough vacuum region. The DHE-IF consists of two funnel-shaped helix electrodes. There are almost no potential "traps" along the central axis of DHE-IF due to the continuous double-helix electrode structure compared to the stacked ring ion funnel. The electrode design of the DHE-IF assembly was guided by ion trajectory simulations. After being fabricated, DHE-IF was integrated into an ESI-TOF-MS platform for tests. A conventional stacked ring ion funnel (IF) was also tested for comparison. The experimental results showed that DHE-IF extended the transmission window of the IF and improved the efficiency of the simultaneous transferring of low and medium m/z ions. In addition, the intensities of caffeine ions (m/z = 195) and reserpine ions (m/z = 609) were enhanced by more than 50% and 10%, respectively. These values were compared with the results obtained by the IF. The DHE-IF is expected to be widely used as an ion import device in MS instruments, which is due to its improved performance and advantages in, e.g., integration and power supply design.

Ion Source Complementarity for Characterization of Complex Organic Mixtures Using Fourier Transform Mass Spectrometry: A Review

Complex organic mixtures are found in many areas of research, such as energy, environment, health, planetology, and cultural heritage, to name but a few. However, due to their complex chemical composition, which holds an extensive potential of information at the molecular level, their molecular characterization is challenging. In mass spectrometry, the ionization step is the key step, as it determines which species will be detected. This review presents an overview of the main ionization sources employed to characterize these kinds of samples in Fourier transform mass spectrometry (FT-MS), namely electrospray (ESI), atmospheric pressure photoionization (APPI), atmospheric pressure chemical ionization (APCI), atmospheric pressure laser ionization (APLI), and (matrix-assisted) laser desorption ionization ((MA)LDI), and their complementarity in the characterization of complex organic mixtures. First, the ionization techniques are examined in the common direct introduction (DI) usage. Second, these approaches are discussed in the context of coupling chromatographic techniques such as gas chromatography, liquid chromatography, and supercritical fluid chromatography.

Connecting the dots: investigating the link between environmental, genetic, and epigenetic influences in metabolomic alterations in oral squamous cell carcinoma

Oral squamous cell carcinoma (OSCC) accounts for around 90% of all oral cancers and is the eighth most common cancer worldwide. Despite progress in managing OSCC, the overall prognosis remains poor, with a survival rate of around 50-60%, largely due to tumor size and recurrence. The challenges of late-stage diagnosis and limitations in current methods emphasize the urgent need for less invasive techniques to enable early detection and treatment, crucial for improving outcomes in this aggressive form of oral cancer. Research is currently aimed at unraveling tumor-specific metabolite profiles to identify candidate biomarkers as well as discover underlying pathways involved in the onset and progression of cancer that could be used as new targets for diagnostic and therapeutic purposes. Metabolomics is an advanced technological approach to identify metabolites in different sample types (biological fluids and tissues). Since OSCC promotes metabolic reprogramming influenced by a combination of genetic predisposition and environmental factors, including tobacco and alcohol consumption, and viral infections, the identification of distinct metabolites through screening may aid in the diagnosis of this condition. Moreover, studies have shown the use of metabolites during the catalysis of epigenetic modification, indicating a link between epigenetics and metabolism. In this review, we will focus on the link between environmental, genetic, and epigenetic influences in metabolomic alterations in OSCC. In addition, we will discuss therapeutic targets of tumor metabolism, which may prevent oral tumor growth, metastasis, and drug resistance.

Mass Spectrometry Imaging Techniques: Non-Ambient and Ambient Ionization Approaches

Molecular information can be acquired from sample surfaces in real time using a revolutionary molecular imaging technique called mass spectrometry imaging (MSI). The technique can concurrently provide high spatial resolution information on the spatial distribution and relative proportion of many different compounds. Thus, many scientists have been drawn to the innovative capabilities of the MSI approach, leading to significant focus in various fields during the past few decades. This review describes the sampling protocol, working principle and applications of a few non-ambient and ambient ionization mass spectrometry imaging techniques. The non-ambient techniques include secondary ionization mass spectrometry and matrix-assisted laser desorption ionization, while the ambient techniques include desorption electrospray ionization, laser ablation electrospray ionization, probe electro-spray ionization, desorption atmospheric pressure photo-ionization and femtosecond laser desorption ionization. The review additionally addresses the advantages and disadvantages of ambient and non-ambient MSI techniques in relation to their suitability, particularly for biological samples used in tissue diagnostics. Last but not least, suggestions and conclusions are made regarding the challenges and future prospects of MSI.

Development and validation of a GC Orbitrap-MS method for the analysis of phthalate esters (PAE) and bis(2-ethylhexyl)adipate (DEHA) in atmospheric particles and its application for screening PM2.5 from Curitiba, Brazil

Phthalates or phthalic acid esters (PAE) and bis(2-ethylhexyl)adipate (DEHA) are ubiquitous chemicals often used as plasticisers and additives in many industrial products and are classified as both persistent organic pollutants (POPs) and new emerging pollutants (NEPs). Exposure to these chemicals, especially through inhalation, is linked to a wide range of negative health effects, including endocrine disruption. Air particulate matter (PM) with an aerodynamic diameter ≤ 2.5 μm can be enriched with PAEs and DEHA and if inhaled can cause multi-system human toxicity. Therefore, proper monitoring of PAEs and DEHA in PM is required to assess human exposure to these pollutants. In this work, we developed and validated a new and sensitive gas-chromatography high-resolution mass spectrometry (GC-HRMS) method for targeted analysis of PAEs including dimethyl phthalate (DMP), diethyl phthalate (DEP), di-n-butyl phthalate (DBP), benzyl butyl phthalate (BBP), bis(2-ethylhexyl)adipate (DEHA), bis(2-ethylhexyl)phthalate (DEHP), di-n-octyl phthalate (DOP), in PM. Analytical aspects including sample preparation steps and GC-HRMS parameters, e.g., quadrupole isolation window, to enhance method sensitivity have been assessed. The estimated limit of detection (LODs) of target PAEs and DEHA ranged from 5.5 to 17 pg μL-1, allowing their trace-level detection in PM. Extraction efficiencies of 78-101% were obtained for the target compounds. Low DMP and DEP extraction efficiencies from the spiked filter substrates indicated that significant losses of higher volatility PAEs can occur during the sample collection when filter-based techniques are used. This work is the first targeted method based on GC-Orbitrap MS for PAEs and DEHA in environmental samples. The validated method was successfully applied for the targeted analysis of PAEs and DEHA in PM2.5 samples from the eighth most populous city in Brazil, Curitiba. This work is the first to report DBP, DEHA, DEHP, and DOP in urban PM from Brazil. The observed concentrations of PAEs (up to 29 ng m-3) in PM2.5 from Curitiba may not represent the extent of pollution by these toxic compounds since the analysed samples were collected during a COVID-19 restriction when anthropogenic activities were reduced.

MARS: A Multipurpose Software for Untargeted LC-MS-Based Metabolomics and Exposomics

Untargeted metabolomics is a growing field, in which recent advances in high-resolution mass spectrometry coupled with liquid chromatography (LC-MS) have facilitated untargeted approaches as a result of improvements in sensitivity, mass accuracy, and resolving power. However, a very large amount of data are generated. Consequently, using computational tools is now mandatory for the in-depth analysis of untargeted metabolomics data. This article describes MetAbolomics ReSearch (MARS), an all-in-one vendor-agnostic graphical user interface-based software applying LC-MS analysis to untargeted metabolomics. All of the analytical steps are described (from instrument data conversion and processing to statistical analysis, annotation/identification, quantification, and preliminary biological interpretation), and tools developed to improve annotation accuracy (e.g., multiple adducts and in-source fragmentation detection, trends across samples, and the MS/MS validator) are highlighted. In addition, MARS allows in-house building of reference databases, to bypass the limits of freely available MS/MS spectra collections. Focusing on the flexibility of the software and its user-friendliness, which are two important features in multipurpose software, MARS could provide new perspectives in untargeted metabolomics data analysis.

Direct introduction MALDI FTICR MS based on dried droplet deposition applied to non-targeted metabolomics on Pisum Sativum root exudates

Non-targeted metabolomic approaches based on direct introduction (DI) through a soft ionization source are nowadays used for large-scale analysis and wide cover-up of metabolites in complex matrices. When coupled with ultra-high-resolution Fourier-Transform ion cyclotron resonance (FTICR MS), DI is generally performed through electrospray (ESI), which, despite the great analytical throughput, can suffer of matrix effects due to residual salts or charge competitors. In alternative, matrix assisted laser desorption ionization (MALDI) coupled with FTICR MS offers relatively high salt tolerance but it is mainly used for imaging of small molecule within biological tissues. In this study, we report a systematic evaluation on the performance of direct introduction ESI and MALDI coupled with FTICR MS applied to the analysis of root exudates (RE), a complex mixture of metabolites released from plant root tips and containing a relatively high salt concentration. Classic dried droplet deposition followed by screening of best matrices and ratio allowed the selection of high ranked conditions for non-targeted metabolomics on RE. Optimization of MALDI parameters led to improved reproducibility and precision. A RE desalted sample was used for comparison on ionization efficiency of the two sources and ion enhancement at high salinity was highlighted in MALDI by spiking desalted solution with inorganic salts. Application of a true lyophilized RE sample exhibited the complementarity of the two sources and the ability of MALDI in the detection of undisclosed metabolites suffering of matrix effects in ESI mode.

Uncovering nasopharyngeal carcinoma from chronic rhinosinusitis and healthy subjects using routine medical tests via machine learning

Nasopharyngeal carcinoma (NPC) is one of the most common types of cancers in South China and Southeast Asia. Clinical data has shown that early detection is essential for improving treatment effectiveness and survival rate. Unfortunately, because the early symptoms of NPC are rather minor and similar to that of diseases such as Chronic Rhinosinusitis (CRS), early detection is a challenge. This paper proposes using machine learning methods to detect NPC using routine medical test data, namely Random Forest (RF), Support Vector Machine (SVM), and Artificial Neural Network (ANN), k-Nearest-Neighbor (KNN) and Logistic Regression (LR). We collected a dataset containing 523 newly diagnosed NPC patients before treatment, 501 newly diagnosed CRS patients before treatment as well as 600 healthy controls. The routine medical test data including age, gender, blood test features, liver function test features, and urine sediment test features. For comparison, we also used data from Epstein-Barr Virus (EBV) antibody tests, which is a specialized test not included among routine medical tests. In our first test, all four methods were tested on classifying NPC vs CRS vs controls; RF gives the best overall performance. Using only routine medical test data, it gives an accuracy of 83.1%, outperforming LR by 12%. In our second test, using only routine medical test data, when classifying NPC vs non-NPC (i.e. CRS or controls), RF achieves an accuracy of 88.2%. In our third test, when classifying NPC vs. controls, RF using only routine test data achieves an accuracy significantly better than RF using only EBV antibody data. Finally, in our last test, RF trained with NPC vs controls, using routine test data only, continued to perform well on an entirely separate dataset. This is a promising result because preliminary NPC detection using routine medical data is easy and inexpensive to implement. We believe this approach will play an important role in the detection and treatment of NPC in the future.

Untargeted LC-HRMS Based-Plasma Metabolomics Reveals 3-O-Methyldopa as a New Biomarker of Poor Prognosis in High-Risk Neuroblastoma

Neuroblastoma (NB) is the most common extracranial malignant tumor in children. Although the survival rate of NB has improved over the years, the outcome of NB still remains poor for over 30% of cases. A more accurate risk stratification remains a key point in the study of NB and the availability of novel prognostic biomarkers of "high-risk" at diagnosis could help improving patient stratification and predicting outcome. In this paper we show a biomarker discovery approach applied to the plasma of 172 NB patients. Plasma samples from a first cohort of NB patients and age-matched healthy controls were used for untargeted metabolomics analysis based on high-resolution mass spectrometry (HRMS). Differential expression analysis highlighted a number of metabolites annotated with a high degree of identification. Among them, 3-O-methyldopa (3-O-MD) was validated in a second cohort of NB patients using a targeted metabolite profiling approach and its prognostic potential was also analyzed by survival analysis on patients with 3 years follow-up. High expression of 3-O-MD was associated with worse prognosis in the subset of patients with stage M tumor (log-rank p < 0.05) and, among them, it was confirmed as a prognostic factor able to stratify high-risk patients older than 18 months. 3-O-MD might be thus considered as a novel prognostic biomarker of NB eligible to be included at diagnosis among catecholamine metabolite panels in prospective clinical studies. Further studies are warranted to exploit other potential biomarkers highlighted using our approach.

Infrared multiple photon dissociation (IRMPD) spectroscopy and its potential for the clinical laboratory

Infrared multiple photon dissociation (IRMPD) spectroscopy is a powerful tool used to probe the vibrational modes-and, by extension, the structure-of an ion within an ion trap mass spectrometer. Compared to traditional FTIR spectroscopy, IRMPD spectroscopy has advantages including its sensitivity and its relative ability to handle complex mixtures. While IRMPD has historically been a technique for fundamental analyses, it is increasingly being applied in a more analytical fashion. Notable recent demonstrations pertinent to the clinical laboratory and adjacent interests include analysis of modified amino acids/residues and carbohydrates, structural elucidation (including isomeric differentiation) of metabolites, identification of novel illicit drugs, and structural studies of various biomolecules and pharmaceuticals. Improvements in analysis time, coupling to commercial instruments, and integration with separations methods are all drivers toward the realization of these analytical applications. Additional improvements in these areas, along with advances in benchtop tunable IR sources and increased cross-discipline collaboration, will continue to drive innovation and widespread adoption. The goal of this tutorial article is to briefly present the fundamentals and instrumentation of IRMPD spectroscopy, as an overview of the utility of this technique for helping to answer questions relevant to clinical analysis, and to highlight limitations to widespread adoption, as well as promising directions in which the field may be heading.

Comparison of High-Resolution Fourier Transform Mass Spectrometry Platforms for Putative Metabolite Annotation

Fourier transform ion cyclotron resonance (FT-ICR) and Orbitrap mass spectrometry (MS) are among the highest-performing analytical platforms used in metabolomics. Non-targeted metabolomics experiments, however, yield extremely complex datasets that make metabolite annotation very challenging and sometimes impossible. The high-resolution accurate mass measurements of the leading MS platforms greatly facilitate this process by reducing mass errors and spectral overlaps. When high resolution is combined with relative isotopic abundance (RIA) measurements, heuristic rules, and constraints during searches, the number of candidate elemental formula(s) can be significantly reduced. Here, we evaluate the performance of Orbitrap ID-X and 12T solariX FT-ICR mass spectrometers in terms of mass accuracy and RIA measurements and how these factors affect the assignment of the correct elemental formulas in the metabolite annotation pipeline. Quality of the mass measurements was evaluated under various experimental conditions (resolution: 120, 240, 500 K; automatic gain control: 5 × 104, 1 × 105, 5 × 105) for the Orbitrap MS platform. High average mass accuracy (<1 ppm for UPLC-Orbitrap MS and <0.2 ppm for direct infusion FT-ICR MS) was achieved and allowed the assignment of correct elemental formulas for over 90% (m/z 75-466) of the 104 investigated metabolites. 13C1 and 18O1 RIA measurements further improved annotation certainty by reducing the number of candidates. Overall, our study provides a systematic evaluation for two leading Fourier transform (FT)-based MS platforms utilized in metabolite annotation and provides the basis for applying these, individually or in combination, to metabolomics studies of biological systems.

Characterization of Protonated Substituted Ureas by Using Diagnostic Gas-Phase Ion-Molecule Reactions Followed by Collision-Activated Dissociation in Tandem Mass Spectrometry Experiments

Substituted ureas correspond to a class of organic compounds commonly used in agricultural and chemical fields. However, distinguishing between different ureas and differentiating substituted ureas from other compounds with similar structures, such as amides, N-oxides, and carbamates, are challenging. In this paper, a four-stage tandem mass spectrometry method (MS⁴) is introduced for this purpose. This method is based on gas-phase ion-molecule reactions of isolated, protonated analytes ([M + H]⁺) with tris(dimethylamino)borane (TDMAB) (MS²) followed by subjecting a diagnostic product ion to two steps of collision-activated dissociation (CAD) (MS³ and MS⁴). All the analyte ions reacted with TDMAB to form a product ion [M + H + TDMAB - HN(CH₃)₂]⁺. The product ion formed for substituted ureas and amides eliminated another HN(CH₃)₂ molecule upon CAD to generate a fragment ion [M + H + TDMAB - 2HN(CH₃)₂]⁺, which was not observed for many other analytes, such as N-oxides, sulfoxides, and pyridines (studied previously). When the [M + H + TDMAB - 2HN(CH₃)₂]⁺ fragment ion was subjected to CAD, different fragment ions were generated for ureas, amides, and carbamates. Fragment ions diagnostic for the ureas were formed via elimination of R-N═C═O (R = hydrogen atom or a substituent), which enabled the differentiation of ureas from amides and carbamates. Furthermore, these fragment ions can be utilized to classify differently substituted ureas. Quantum chemical calculations were employed to explore the mechanisms of the reactions. The limit of detection for the diagnostic ion-molecule reaction product ion in HPLC/MS² experiments was found to range from 20 to 100 nM.

Environmental metal toxicity assessment by the combined application of metallomics and metabolomics

The growing interest of our society for the environment, climate change, and the assurance of the quality of life and health has been the motor of new methodological proposals that allow a more comprehensive knowledge of the problems to be solved. In this sense, the potential of omic methodologies to study these problems from a global perspective represents a milestone in environmental studies. Therefore, the study of essential and toxic metals has a special interest, particularly in relation to toxicity issues and their association to biological interactions, transport, binding to biomolecules, and behavior in biological interfaces. These studies have promoted new instrumental platforms and methodological approaches that allow addressing these problems. Furthermore, to encompass the reality of molecule-atoms interactions in their completeness, combinations of omics have been tried, focusing on environment, food, and health issues. In this sense, the present work is situated, with the objective of reviewing the most recent methodological proposals in the field of the environment and their applications, considering not only the analytical approaches but also how they have to be applied, the use of bioindicators' exposure experiments in the laboratory, and the potential transfer of the findings from the laboratory to the field. This latter point is a true touchstone, which makes these new analytical methodologies in the necessary tools for understanding the environment and the consequences of its imbalance.

In situ detection and imaging of lysophospholipids in zebrafish using matrix-assisted laser desorption/ionization Fourier transform ion cyclotron resonance mass spectrometry

In this paper, a matrix-assisted laser desorption/ionization (MALDI) Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS) (MALDI-FTICR-MS) imaging method was developed to rapid and in situ detect the spatial distribution of lysophospholipids (LPLs) in zebrafish. The combination of MALDI with ultrahigh-resolution FTICR-MS achieves the MS imaging of LPLs with a mass resolution up to 50 000, which allows accurate identification and clear spatial visualization of LPLs in complex biological tissues. A series of lysophosphatidylcholines (LPCs) was detected using positive ion detection mode, and their concentration differences and spatial distributions were clearly visualized in different parts of zebrafish tissue. The method is rapid, simple, and efficient, being a desirable way to understand the spatial distribution of LPLs in biosome.

Expanding the Scope of Detectable Microbial Natural Products by Complementary Analytical Methods and Cultivation Systems

Recent advances in genome sequencing have unveiled a large discrepancy between the genome-encoded capacity of microorganisms to produce secondary metabolites and the number detected. In this work, a two-platform mass spectrometry analysis for the comprehensive secondary metabolomics characterization of nine myxobacterial strains, focusing on extending the range of detectable secondary metabolites by diversifying analytical methods and cultivation conditions, is presented. Direct infusion measurements of crude extracts on a Fourier transform ion cyclotron resonance mass spectrometer are compared to a time-of-flight device coupled to liquid chromatography measurements. Both methods are successful in detecting known metabolites, whereas statistical analysis of unknowns highlights their complementarity: Strikingly, 82-99% of molecular features detected with one setup were not detectable with the other. Metabolite profile differences from our set of strains grown in liquid culture versus their swarming colonies on agar plates were evaluated. The detection of up to 96% more molecular features when both liquid and plate cultures were analyzed translates into increased chances to identify new secondary metabolites. Discrimination between primary and secondary metabolism in combination with GNPS molecular networking revealed strain Mx3 as particularly promising for the isolation of novel secondary metabolites among the nine strains investigated in this study.

Mass shift in mass spectrometry imaging: comprehensive analysis and practical corrective workflow

MALDI mass spectrometry imaging (MSI) allows the mapping and the tentative identification of compounds based on their m/z value. In typical MSI, a spectrum is taken at incremental 2D coordinates (pixels) across a sample surface. Single pixel mass spectra show the resolving power of the mass analyzer. Mass shift, i.e., variations of the m/z of the same ion(s), may occur from one pixel to another. The superposition of shifted masses from individual pixels peaks apparently degrades the resolution and the mass accuracy in the average spectrum. This leads to low confidence annotations and biased localization in the image. Besides the intrinsic performances of the analyzer, the sample properties (local composition, thickness, matrix deposition) and the calibration method are sources of mass shift. Here, we report a critical analysis and recommendations to mitigate these sources of mass shift. Mass shift 2D distributions were mapped to illustrate its effect and explore systematically its origin. Adapting the sample preparation, carefully selecting the data acquisition settings, and wisely applying post-processing methods (i.e., m/z realignment or individual m/z recalibration pixel by pixel) are key factors to lower the mass shift and to improve image quality and annotations. A recommended workflow, resulting from a comprehensive analysis, was successfully applied to several complex samples acquired on both MALDI ToF and MALDI FT-ICR instruments.

Pyrene Tags for the Detection of Carbohydrates by Label-Assisted Laser Desorption/Ionisation Mass Spectrometry*

Matrix-assisted laser desorption/ionisation mass spectrometry (MALDI-MS) is widely used for the analysis of biomolecules. Label-assisted laser desorption/ionisation mass spectrometry (LALDI-MS) is a matrix-free variant of MALDI-MS, in which only analytes covalently attached to a laser desorption/ionisation (LDI) enhancer are detected. LALDI-MS has shown promise in overcoming the limitations of MALDI-MS in terms of sample preparation and MS analysis. In this work, we have developed a series of pyrene-based LDI reagents (LALDI tags) that can be used for labelling and LALDI-MS analysis of reducing carbohydrates from complex (biological) samples without the need for additional chemical derivatisation or purification. We have systematically explored the suitability of four pyrene-based LDI enhancers and three aldehyde-reactive handles, optimised sample preparation, and demonstrated the use of LALDI tags for the detection of lactose. We have also exemplified the potential of LALDI tags for labelling carbohydrates in biological samples by direct detection of lactose in cow's milk. These results demonstrate that LALDI-MS is a promising technique for the analysis of reducing carbohydrates in biological samples, and pave the way for the development of LALDI-MS for glycomics and diagnostics.

Analysis of the metabolic switch induced by the spirulina peptide SP6 in high fat diet ApoE-/- mice model: A direct infusion FT-ICR-MS based approach

Atherosclerosis, dyslipidemia and hypertension are comorbid diseases often found in combination. Among different pharmacological approaches the employment of natural multifunctional peptides is an attractive option as side therapy. Mass spectrometry-based metabolomics provide valuable information on metabolic changes and can be useful to elucidate peptide pharmacodynamics. In this this work we performed a preliminary investigation on the potential effect of a recently characterized Spirulina platensis peptide named SP6 (GIVAGDVTPI) on the modulation of metabolism in a high fat diet ApoE^-/- mice atherosclerotic model. A direct infusion Fourier transform ion cyclotron resonance mass spectrometry (DI-FT-ICR-MS) approach was used to elucidate polar and non-polar metabolites extracted by mice plasma following four weeks SP6 treatment. The method delivered fast analysis time, repeatability, high mass accuracy and resolution for unambiguous molecular formula assignment. Multivariate statistical analysis (PLS-DA) highlighted a clear class separation, revealing the alteration of numerous metabolites levels belonging to different classes. In particular sphingolipids, glycerophospholipids, TCA cycle intermediates, and amino acids, which are key players in the atherosclerotic process and progression, were upregulated in saline alone HFD ApoE^-/- group, while were sensibly decreased after treatment with SP6 peptide. These results could open the way to further, large-scale, investigation of SP6 peptide effects in the regulation of atherosclerotic disease development and progression, and show the potential of DI-FT-ICR as fast analytical tool to take snaphshots of metabolic changes before moving to targeted MS-based approaches.

Ultrahigh-Resolution Mass Spectrometry-Based Platform for Plasma Metabolomics Applied to Type 2 Diabetes Research

Metabolomics-the endpoint of the omics cascade-is increasingly recognized as a preferred method for understanding the ultimate responses of biological systems to stress. Flow injection electrospray (FIE) mass spectrometry (MS) has advantages for untargeted metabolic fingerprinting due to its simplicity and capability for high-throughput screening but requires a high-resolution mass spectrometer to resolve metabolite features. In this study, we developed and validated a high-throughput and highly reproducible metabolomics platform integrating FIE with ultrahigh-resolution Fourier transform ion cyclotron resonance (FTICR) MS for analysis of both polar and nonpolar metabolite features from plasma samples. FIE-FTICR MS enables high-throughput detection of hundreds of metabolite features in a single mass spectrum without a front-end separation step. Using plasma samples from genetically identical obese mice with or without type 2 diabetes (T2D), we validated the intra and intersample reproducibility of our method and its robustness for simultaneously detecting alterations in both polar and nonpolar metabolite features. Only 5 min is needed to acquire an ultra-high resolution mass spectrum in either a positive or negative ionization mode. Approximately 1000 metabolic features were reproducibly detected and annotated in each mouse plasma group. For significantly altered and highly abundant metabolite features, targeted tandem MS (MS/MS) analyses can be applied to confirm their identity. With this integrated platform, we successfully detected over 300 statistically significant metabolic features in T2D mouse plasma as compared to controls and identified new T2D biomarker candidates. This FIE-FTICR MS-based method is of high throughput and highly reproducible with great promise for metabolomics studies toward a better understanding and diagnosis of human diseases.

Induced Self-aspiration Electrospray Ionization Mass Spectrometry for Flexible Sampling and Analysis

Electrospray ionization (ESI) operating in pulse mode can enhance the utilization efficiency of the electrospray ions by a mass spectrometer. Herein, a novel ionization technique called induced self-aspiration-electrospray ionization (ISA-ESI) was developed based on self-aspiration sampling and capacitive induction. The sample solution polarized in a strong electric field was pulsed drawn into a capillary that was connected to a subambient chamber. The sample solution with polarized ions forms a charged liquid column, which can initiate an electrospray when reaching the capillary outlet. In addition to the self-aspiration ability, the use of a constant high voltage supply and no electrical contact with the solution can also simplify the sampling and ionization operation, enabling a convenient ESI mass spectrometry analysis. The developed ISA-ESI source has been used for multidimensional monitoring of chemical reactions as well as liquid extraction surface analysis of plant tissues. It was expected that this special ionization method could be extended to automated high-throughput ESI-MS analysis.

Parallel Detection of Fundamental and Sixth Harmonic Signals Using an ICR Cell with Dipole and Sixth Harmonic Detectors

Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) is a powerful instrument for high-resolution analysis of biomolecules. However, relatively long signal acquisition periods are needed to achieve mass spectra with high resolution. The use of multiple detector electrodes for detection of harmonic frequencies has been introduced as one approach to increase scan rate for a given resolving power or to obtain increased resolving power for a given detection period. The achieved resolving power and scan rate increase linearly with the order of detected harmonic signals. In recent years, ICR cell geometries have been investigated to increase the order of the harmonic frequencies and enhance harmonic signal intensities. In this study, we demonstrated PCB-based ICR cell designs with dipole and sixth harmonic detectors for parallel detection of fundamental and harmonic (6f) signals. The sixth harmonic signals from the sixth harmonic detector showed an expected 6 times higher resolving power with (M + 3H)3+ charge state insulin ions as compared with that from fundamental signals from the dipole detector. Moreover, the insulin isotopic peaks with sixth harmonic frequency signals acquired with the sixth harmonic detector were resolved for a 40 ms data acquisition period but unresolved with the same duration dipole detector signals, corresponding to a 6-fold improvement in achievable spectral acquisition rates for a given resolving power.

Metabolomics technology and bioinformatics for precision medicine

Precision medicine is rapidly emerging as a strategy to tailor medical treatment to a small group or even individual patients based on their genetics, environment and lifestyle. Precision medicine relies heavily on developments in systems biology and omics disciplines, including metabolomics. Combination of metabolomics with sophisticated bioinformatics analysis and mathematical modeling has an extreme power to provide a metabolic snapshot of the patient over the course of disease and treatment or classifying patients into subpopulations and subgroups requiring individual medical treatment. Although a powerful approach, metabolomics have certain limitations in technology and bioinformatics. We will review various aspects of metabolomics technology and bioinformatics, from data generation, bioinformatics analysis, data fusion and mathematical modeling to data management, in the context of precision medicine.

MolFind2: A Protocol for Acquiring and Integrating MS3 Data to Improve In Silico Chemical Structure Elucidation for Metabolomics

Structure elucidation of metabolites (<1000 Da) in biofluids is extremely challenging due to the diversity and complexity of chemical structure space. Generally, due to lack of reference tandem mass data (MS²), in silico fragmenters are used to rank candidates acquired from chemical databases as a function on how well they explain an experimental collision-induced dissociation spectrum. However, multistage fragmentation data (i.e., MS³) have not been adequately utilized in current metabolomics structure elucidation pipelines. To address this shortcoming, here we describe an experimental (nontargeted direct infusion ion mobility-mass spectrometry-based) and computational workflow to acquire and utilize multistage mass (MS³) spectrometry data for database-assisted structure elucidation.

Pushing the analytical limits: new insights into complex mixtures using mass spectra segments of constant ultrahigh resolving power

A new strategy has been developed for characterization of the most challenging complex mixtures to date, using a combination of custom-designed experiments and a new data pre-processing algorithm. In contrast to traditional methods, the approach enables operation of Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) with constant ultrahigh resolution at hitherto inaccessible levels (approximately 3 million FWHM, independent of m/z). The approach, referred to as OCULAR, makes it possible to analyze samples that were previously too complex, even for high field FT-ICR MS instrumentation. Previous FT-ICR MS studies have typically spanned a broad mass range with decreasing resolving power (inversely proportional to m/z) or have used a single, very narrow m/z range to produce data of enhanced resolving power; both methods are of limited effectiveness for complex mixtures spanning a broad mass range, however. To illustrate the enhanced performance due to OCULAR, we show how a record number of unique molecular formulae (244 779 elemental compositions) can be assigned in a single, non-distillable petroleum fraction without the aid of chromatography or dissociation (MS/MS) experiments. The method is equally applicable to other areas of research, can be used with both high field and low field FT-ICR MS instruments to enhance their performance, and represents a step-change in the ability to analyze highly complex samples.

Optimized Reconstruction Techniques for Multiplexed Dual-Gate Ion Mobility Mass Spectrometry Experiments

When coupling drift-tube gas-phase ion mobility separations with ion trapping mass analyzers an integrative, stepped approach to spectral reconstruction is a logical, yet highly inefficient means to determine gas-phase mobility coefficients. This experimental mode is largely predicated on the respective time scales of the two techniques each requiring tens of milliseconds to complete under routine conditions. Multiplexing techniques, such as Fourier and Hadamard based techniques, are a potential solution but still require extended experimental times that are not fully compatible with modern front-end separation schemes. Using a basis pursuit denoising (BPDN) approach to deconvolute Fourier transform ion mobility mass spectrometry (FT-IMMS) drift time spectra, we demonstrate significant time savings while maintaining a high degree of spectral resolution and signal-to-noise ratio. Under ideal conditions, the FT-IMMS operates with increased ion transmission (up to 25%); however, the linear chirp that spans into the kHz range often leads to significant levels of ion gate depletion, which limit both resolving power and ion transmission. The method proposed in this manuscript demonstrates the potential to reduce IMS acquisition time while simultaneously maximizing spectral resolution at longer effective gate pulse widths compared to the traditional set of multiplexing and signal averaging experiments.

A Framework for Development of Useful Metabolomic Biomarkers and Their Effective Knowledge Translation

Despite the significant advantages of metabolomic biomarkers, no diagnostic tests based on metabolomics have been introduced to clinical use. There are many reasons for this, centered around substantial obstacles in developing clinically useful metabolomic biomarkers. Most significant is the need for interdisciplinary teams with expertise in metabolomics, analysis of complex clinical and metabolomic data, and clinical care. Importantly, the clinical need must precede biomarker discovery, and the experimental design for discovery and validation must reflect the purpose of the biomarker. Standard operating procedures for procuring and handling samples must be developed from the beginning, to ensure experimental integrity. Assay design is another challenge, as there is not much precedent informing this. Another obstacle is that it is not yet clear how to protect any intellectual property related to metabolomic biomarkers. Viewing a metabolomic biomarker as a natural phenomenon would inhibit patent protection and potentially stifle commercial interest. However, demonstrating that a metabolomic biomarker is actually a derivative of a natural phenomenon that requires innovation would enhance investment in this field. Finally, effective knowledge translation strategies must be implemented, which will require engagement with end users (clinicians and lab physicians), patient advocate groups, policy makers, and payer organizations. Addressing each of these issues comprises the framework for introducing a metabolomic biomarker to practice.

Fast Profiling of Natural Pigments in Different Spirulina (Arthrospira platensis) Dietary Supplements by DI-FT-ICR and Evaluation of their Antioxidant Potential by Pre-Column DPPH-UHPLC Assay

Arthrospira platensis, better known as Spirulina, is one of the most important microalgae species. This cyanobacterium possesses a rich metabolite pattern, including high amounts of natural pigments. In this study, we applied a combined strategy based on Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FT-ICR-MS) and Ultra High-Performance Liquid Chromatography (UHPLC) for the qualitative/quantitative characterization of Spirulina pigments in three different commercial dietary supplements. FT-ICR was employed to elucidate the qualitative profile of Spirulina pigments, in both direct infusion mode (DIMS) and coupled to UHPLC. DIMS showed to be a very fast (4 min) and accurate (mass accuracy ≤ 0.01 ppm) tool. 51 pigments were tentatively identified. The profile revealed different classes, such as carotenes, xanthophylls and chlorophylls. Moreover, the antioxidant evaluation of the major compounds was assessed by pre-column reaction with the DPPH radical followed by fast UHPLC-PDA separation, highlighting the contribution of single analytes to the antioxidant potential of the entire pigment fraction. β-carotene, diadinoxanthin and diatoxanthin showed the highest scavenging activity. The method took 40 min per sample, comprising reaction. This strategy could represent a valid tool for the fast and comprehensive characterization of Spirulina pigments in dietary supplements, as well as in other microalgae-based products.

Moving beyond the van Krevelen Diagram: A New Stoichiometric Approach for Compound Classification in Organisms

van Krevelen diagrams (O/C vs H/C ratios of elemental formulas) have been widely used in studies to obtain an estimation of the main compound categories present in environmental samples. However, the limits defining a specific compound category based solely on O/C and H/C ratios of elemental formulas have never been accurately listed or proposed to classify metabolites in biological samples. Furthermore, while O/C vs H/C ratios of elemental formulas can provide an overview of the compound categories, such classification is inefficient because of the large overlap among different compound categories along both axes. We propose a more accurate compound classification for biological samples analyzed by high-resolution mass spectrometry based on an assessment of the C/H/O/N/P stoichiometric ratios of over 130 000 elemental formulas of compounds classified in 6 main categories: lipids, peptides, amino sugars, carbohydrates, nucleotides, and phytochemical compounds (oxy-aromatic compounds). Our multidimensional stoichiometric compound classification (MSCC) constraints showed a highly accurate categorization of elemental formulas to the main compound categories in biological samples with over 98% of accuracy representing a substantial improvement over any classification based on the classic van Krevelen diagram. This method represents a signficant step forward in environmental research, especially ecological stoichiometry and eco-metabolomics studies, by providing a novel and robust tool to improve our understanding of the ecosystem structure and function through the chemical characterization of biological samples.

Biomarker Discovery in Animal Health and Disease: The Application of Post-Genomic Technologies

The causes of many important diseases in animals are complex and multifactorial, which present unique challenges. Biomarkers indicate the presence or extent of a biological process, which is directly linked to the clinical manifestations and outcome of a particular disease. Identifying biomarkers or biomarker profiles will be an important step towards disease characterization and management of disease in animals. The emergence of post-genomic technologies has led to the development of strategies aimed at identifying specific and sensitive biomarkers from the thousands of molecules present in a tissue or biological fluid. This review will summarize the current developments in biomarker discovery and will focus on the role of transcriptomics, proteomics and metabolomics in biomarker discovery for animal health and disease.

Visualization of 57Fe-Labeled Heme Isotopic Fine Structure and Localization of Regions of Erythroblast Maturation in Mouse Spleen by MALDI FTICR-MS Imaging

Epoetin beta pegol (continuous erythropoiesis receptor activator; C.E.R.A.), or methoxy-polyethylene glycol-modified epoetin beta, is a long-acting erythropoiesis stimulating agent (ESA) that effectively maintains hemoglobin levels. It promotes proliferation of erythroid progenitor cells in hematopoietic organs and leads to increased reticulocyte and hemoglobin levels. However, the detailed erythropoietic effects of various ESAs on their target organs have yet to be clarified, and new approaches are needed to analyze tissue iron localization with structural information. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) techniques are widely used in basic pharmaceutical research. High-resolution Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS) imaging enables the spatial mapping and identification of biomolecules. In this study, mice administered with C.E.R.A. were fed a diet containing the stable iron isotope ⁵⁷Fe. The ⁵⁷Fe-heme⁺ isotopic fine structure peak (m/z 617.1772) was separated from the non-labeled heme⁺ isotopic peak (Δ0.0029) by FTICR-MS with a resolving power of more than 500,000. We optimized the platform to analyze the distribution of ⁵⁷Fe-heme in the spleen using MALDI FTICR-MS imaging. The combination of the ultrahigh resolution power of FTICR-MS and a stable isotope labeling technique has the potential to be very effective in basic pharmaceutical research. Graphical Abstract ᅟ.

Foodomics and Food Safety: Where We Are

The power of foodomics as a discipline that is now broadly used for quality assurance of food products and adulteration identification, as well as for determining the safety of food, is presented. Concerning sample preparation and application, maintenance of highly sophisticated instruments for both high-performance and high-throughput techniques, and analysis and data interpretation, special attention has to be paid to the development of skilled analysts. The obtained data shall be integrated under a strong bioinformatics environment. Modern mass spectrometry is an extremely powerful analytical tool since it can provide direct qualitative and quantitative information about a molecule of interest from only a minute amount of sample. Quality of this information is influenced by the sample preparation procedure, the type of mass spectrometer used and the analyst's skills. Technical advances are bringing new instruments of increased sensitivity, resolution and speed to the market. Other methods presented here give additional information and can be used as complementary tools to mass spectrometry or for validation of obtained results. Genomics and transcriptomics, as well as affinity-based methods, still have a broad use in food analysis. Serious drawbacks of some of them, especially the affinity-based methods, are the cross-reactivity between similar molecules and the influence of complex food matrices. However, these techniques can be used for pre-screening in order to reduce the large number of samples. Great progress has been made in the application of bioinformatics in foodomics. These developments enabled processing of large amounts of generated data for both identification and quantification, and for corresponding modeling.

Metabolomics for Plant Improvement: Status and Prospects

Post-genomics era has witnessed the development of cutting-edge technologies that have offered cost-efficient and high-throughput ways for molecular characterization of the function of a cell or organism. Large-scale metabolite profiling assays have allowed researchers to access the global data sets of metabolites and the corresponding metabolic pathways in an unprecedented way. Recent efforts in metabolomics have been directed to improve the quality along with a major focus on yield related traits. Importantly, an integration of metabolomics with other approaches such as quantitative genetics, transcriptomics and genetic modification has established its immense relevance to plant improvement. An effective combination of these modern approaches guides researchers to pinpoint the functional gene(s) and the characterization of massive metabolites, in order to prioritize the candidate genes for downstream analyses and ultimately, offering trait specific markers to improve commercially important traits. This in turn will improve the ability of a plant breeder by allowing him to make more informed decisions. Given this, the present review captures the significant leads gained in the past decade in the field of plant metabolomics accompanied by a brief discussion on the current contribution and the future scope of metabolomics to accelerate plant improvement.

Static harmonization of dynamically harmonized Fourier transform ion cyclotron resonance cell

Static harmonization in the Fourier transform ion cyclotron resonance cell improves the resolving power of the cell and prevents dephasing of the ion cloud in the case of any trajectory of the charged particle, not necessarily axisymmetric cyclotron (as opposed to dynamic harmonization). We reveal that the Fourier transform ion cyclotron resonance cell with dynamic harmonization (paracell) is proved to be statically harmonized. The volume of the statically harmonized potential distribution increases with an increase in the number of trap segments.

Application of mass spectrometry in the characterization of chemicals in coal-derived liquids

Coal-derived liquids (CDLs) are primarily generated from pyrolysis, carbonization, gasification, direct liquefaction, low-temperature extraction, thermal dissolution, and mild oxidation. CDLs are important feedstocks for producing value-added chemicals and clean liquid fuels as well as high performance carbon materials. Accordingly, the compositional characterization of chemicals in CDLs at the molecular level with advanced analytical techniques is significant for the efficient utilization of CDLs. Although reviews on advancements have been rarely reported, great progress has been achieved in this area by using gas chromatography/mass spectrometry (GC/MS), two-dimensional GC-time of flight mass spectrometry (GC × GC-TOFMS), and Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). This review focuses on characterizing hydrocarbon, oxygen-containing, nitrogen-containing, sulfur-containing, and halogen-containing chemicals in various CDLs with these three mass spectrometry techniques. Small molecular (< 500 u), volatile and semi-volatile, and less polar chemicals in CDLs have been identified with GC/MS and GC × GC-TOFMS. By equipped with two-dimensional GC, GC × GC-TOFMS can achieve a clearly chromatographic separation of complex chemicals in CDLs without prior fractionation, and thus can overcome the disadvantages of co-elution and serious peak overlap in GC/MS analysis, providing much more compositional information. With ultrahigh resolving power and mass accuracy, FT-ICR MS reveals a huge number of compositionally distinct compounds assigned to various chemical classes in CDLs. It shows excellent performance in resolving and characterizing higher-molecular, less volatile, and polar chemicals that cannot be detected by GC/MS and GC × GC-TOFMS. The application of GC × GC-TOFMS and FT-ICR MS to chemical characterization of CDLs is not as prevalent as that of petroleum and largely remains to be developed in many respects. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 36:543-579, 2017.

A Diet Diverse in Bamboo Parts is Important for Giant Panda (Ailuropoda melanoleuca) Metabolism and Health

The aim of this study was to determine the metabolic response in giant pandas (Ailuropoda melanoleuca) to the consumption of certain parts of bamboo above ground growth. Giant pandas were provisioned with three species of bamboo: Phyllostachys bissetii, of which they only consume the culm (culm group); Bashania fargesii, of which they only consume the leaves (leaf group); and Qiongzhuea opienensis, of which they only consume the shoots (shoot group). The “culm” group absorbed the highest amount of calories and fiber, but was in short energy supply (depressed tricarboxylic acid cycle activity), and high fiber level diet might reduce the digestibility of protein. The “culm” and “leaf” groups absorbed less protein, and had a lower rate of body mass growth than the “shoot” group. Digestion of fiber requires energy input and yields low caloric extraction from the culm and leaf, and protein intake is important for increasing body mass. However, long-term consumption of shoots may have a potentially negative effect on the health because of high protein composition. Therefore, a balanced diet consisting of diverse plant parts of bamboo is important for the overall metabolic function and health of captive giant pandas.

Plant lipidomics at the crossroads: From technology to biology driven science

The identification and quantification of lipids from plant tissues have become commonplace and many researchers now incorporate lipidomics approaches into their experimental studies. Plant lipidomics research continues to involve technological developments such as those in mass spectrometry imaging, but in large part, lipidomics approaches have matured to the point of being accessible to the novice. Here we review some important considerations for those planning to apply plant lipidomics to their biological questions, and offer suggestions for appropriate tools and practices. This article is part of a Special Issue entitled: BBALIP_Lipidomics Opinion Articles edited by Sepp Kohlwein.

Metabolomics: A Primer

Metabolomics generates a profile of small molecules that are derived from cellular metabolism and can directly reflect the outcome of complex networks of biochemical reactions, thus providing insights into multiple aspects of cellular physiology. Technological advances have enabled rapid and increasingly expansive data acquisition with samples as small as single cells; however, substantial challenges in the field remain. In this primer we provide an overview of metabolomics, especially mass spectrometry (MS)-based metabolomics, which uses liquid chromatography (LC) for separation, and discuss its utilities and limitations. We identify and discuss several areas at the frontier of metabolomics. Our goal is to give the reader a sense of what might be accomplished when conducting a metabolomics experiment, now and in the near future.

Mass spectrometry-based plant metabolomics: Metabolite responses to abiotic stress

Metabolomics is one omics approach that can be used to acquire comprehensive information on the composition of a metabolite pool to provide a functional screen of the cellular state. Studies of the plant metabolome include analysis of a wide range of chemical species with diverse physical properties, from ionic inorganic compounds to biochemically derived hydrophilic carbohydrates, organic and amino acids, and a range of hydrophobic lipid-related compounds. This complexitiy brings huge challenges to the analytical technologies employed in current plant metabolomics programs, and powerful analytical tools are required for the separation and characterization of this extremely high compound diversity present in biological sample matrices. The use of mass spectrometry (MS)-based analytical platforms to profile stress-responsive metabolites that allow some plants to adapt to adverse environmental conditions is fundamental in current plant biotechnology research programs for the understanding and development of stress-tolerant plants. In this review, we describe recent applications of metabolomics and emphasize its increasing application to study plant responses to environmental (stress-) factors, including drought, salt, low oxygen caused by waterlogging or flooding of the soil, temperature, light and oxidative stress (or a combination of them). Advances in understanding the global changes occurring in plant metabolism under specific abiotic stress conditions are fundamental to enhance plant fitness and increase stress tolerance. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 35:620-649, 2016.

Applications of Fourier Transform Ion Cyclotron Resonance (FT-ICR) and Orbitrap Based High Resolution Mass Spectrometry in Metabolomics and Lipidomics

Metabolomics, along with other "omics" approaches, is rapidly becoming one of the major approaches aimed at understanding the organization and dynamics of metabolic networks. Mass spectrometry is often a technique of choice for metabolomics studies due to its high sensitivity, reproducibility and wide dynamic range. High resolution mass spectrometry (HRMS) is a widely practiced technique in analytical and bioanalytical sciences. It offers exceptionally high resolution and the highest degree of structural confirmation. Many metabolomics studies have been conducted using HRMS over the past decade. In this review, we will explore the latest developments in Fourier transform mass spectrometry (FTMS) and Orbitrap based metabolomics technology, its advantages and drawbacks for using in metabolomics and lipidomics studies, and development of novel approaches for processing HRMS data.

Metabolite extraction for high-throughput FTICR-MS-based metabolomics of grapevine leaves

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An improved metabolite extraction method for DI-FTICR metabolomics was developed.

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The number of identified metabolites from grapevine leaves was maximized.

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The extraction method allowed the extraction of polar and non-polar compounds.

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Identified metabolites covered all major classes found in plants.

In metabolomics there is an ever-growing need for faster and more comprehensive analysis methods to cope with the increase of biological studies. Direct infusion Fourier-transform ion cyclotron-resonance mass spectrometry (DI-FTICR-MS) is used in non-targeted metabolomics to obtain high-resolution snapshots of the metabolic state of a system. In any metabolic profiling study, the establishment of an effective metabolite extraction protocol is paramount. We developed an improved metabolite extraction method, compatible with DI-FTICR-MS-based metabolomics, using grapevine leaves. This extraction protocol allowed the extraction of polar and non-polar compounds, covering all major classes found in plants and increasing metabolome coverage.

Understanding Metabolomics in Biomedical Research

The term "omics" refers to any type of specific study that provides collective information on a biological system. Representative omics includes genomics, proteomics, and metabolomics, and new omics is constantly being added, such as lipidomics or glycomics. Each omics technique is crucial to the understanding of various biological systems and complements the information provided by the other approaches. The main strengths of metabolomics are that metabolites are closely related to the phenotypes of living organisms and provide information on biochemical activities by reflecting the substrates and products of cellular metabolism. The transcriptome does not always correlate with the proteome, and the translated proteome might not be functionally active. Therefore, their changes do not always result in phenotypic alterations. Unlike the genome or proteome, the metabolome is often called the molecular phenotype of living organisms and is easily translated into biological conditions and disease states. Here, we review the general strategies of mass spectrometry-based metabolomics. Targeted metabolome or lipidome analysis is discussed, as well as nontargeted approaches, with a brief explanation of the advantages and disadvantages of each platform. Biomedical applications that use mass spectrometry-based metabolomics are briefly introduced.

Diagnostic Metabolomic Blood Tests for Endoluminal Gastrointestinal Cancer--A Systematic Review and Assessment of Quality

Advances in analytics have resulted in metabolomic blood tests being developed for the detection of cancer. This systematic review aims to assess the diagnostic accuracy of blood-based metabolomic biomarkers for endoluminal gastrointestinal (GI) cancer. Using endoscopic diagnosis as a reference standard, methodologic and reporting quality was assessed using validated tools, in addition to pathway-based informatics to biologically contextualize discriminant features. Twenty-nine studies (15 colorectal, 9 esophageal, 3 gastric, and 2 mixed) with data from 10,835 participants were included. All reported significant differences in hematologic metabolites. In pooled analysis, 246 metabolites were found to be significantly different after multiplicity correction. Incremental metabolic flux with disease progression was frequently reported. Two promising candidates have been validated in independent populations (both colorectal biomarkers), and one has been approved for clinical use. Networks analysis suggested modulation of elements of up to half of Edinburgh Human Metabolic Network subdivisions, and that the poor clinical applicability of commonly modulated metabolites could be due to extensive molecular interconnectivity. Methodologic and reporting quality was assessed as moderate-to-poor. Serum metabolomics holds promise for GI cancer diagnostics; however, future efforts must adhere to consensus standardization initiatives, utilize high-resolution discovery analytics, and compare candidate biomarkers with peer nonendoscopic alternatives.

Metabolome analyses in exposome studies: Profiling methods for a vast chemical space

Metabolic profiling (metabonomics/metabolomics) is now used routinely as a tool to provide information-rich datasets for biomarker discovery, prompting and augmenting detailed mechanistic studies. The experimental design and focus of any individual study will be reflected in the types of biomarkers that can be detected; toxicological studies will likely focus on markers of response to insult, whereas clinical case-control studies may yield diagnostic markers of disease. Population studies can make use of omics analyses, including metabonomics, to provide mechanistically-relevant markers that link environmental exposures to chronic disease endpoints. In this article, examples of how metabolic profiling has played a key role in molecular epidemiological analyses of chronic disease are presented, and how these reflect different aspects of the causal pathway. A commentary on the nature of metabolome analysis as a complex mixture problem as opposed to a coded, sequence or template problem is provided, alongside an overview of current and future analytical platforms that are being applied to meet this analytical challenge. Epidemiological studies are an important nexus for integrating various measures of the human exposome, and the ubiquity, diversity and functions of small molecule metabolites, represent an important way to link individual exposures, genetics and phenotype.