BACKGROUND: Different types of analytical methods, with different characteristics, are applied in metabolomics and lipidomics research and include untargeted, targeted and semi-targeted methods. Ultra High Performance Liquid Chromatography-Mass Spectrometry is one of the most frequently applied measurement instruments in metabolomics because of its ability to detect a large number of water-soluble and lipid metabolites over a wide range of concentrations in short analysis times. Methods applied for the detection and quantification of metabolites differ and can either report a (normalised) peak area or an absolute concentration. AIM OF REVIEW: In this tutorial we aim to (1) define similarities and differences between different analytical approaches applied in metabolomics and (2) define how amounts or absolute concentrations of endogenous metabolites can be determined together with the advantages and limitations of each approach in relation to the accuracy and precision when concentrations are reported. KEY SCIENTIFIC CONCEPTS OF REVIEW: The pre-analysis knowledge of metabolites to be targeted, the requirement for (normalised) peak responses or absolute concentrations to be reported and the number of metabolites to be reported define whether an untargeted, targeted or semi-targeted method is applied. Fully untargeted methods can only provide (normalised) peak responses and fold changes which can be reported even when the structural identity of the metabolite is not known. Targeted methods, where the analytes are known prior to the analysis, can also report fold changes. Semi-targeted methods apply a mix of characteristics of both untargeted and targeted assays. For the reporting of absolute concentrations of metabolites, the analytes are not only predefined but optimized analytical methods should be developed and validated for each analyte so that the accuracy and precision of concentration data collected for biological samples can be reported as fit for purpose and be reviewed by the scientific community.
- Keywords
- Metabolomics, Quantification, Semi-targeted, Targeted, UHPLC-MS, Untargeted, Validation,
- MeSH
- Mass Spectrometry * methods MeSH
- Humans MeSH
- Metabolomics * methods MeSH
- Chromatography, High Pressure Liquid methods MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Review MeSH
OBJECTIVES: Metabolomics aims for comprehensive characterization and measurement of small molecule metabolites (<1700 Da) in complex biological matrices. This study sought to assess the current understanding and usage of metabolomics in laboratory medicine globally and evaluate the perception of its promise and future implementation. METHODS: A survey was conducted by the IFCC metabolomics working group that queried 400 professionals from 79 countries. Participants provided insights into their experience levels, knowledge, and usage of metabolomics approaches, along with detailing the applications and methodologies employed. RESULTS: Findings revealed a varying level of experience among respondents, with varying degrees of familiarity and utilization of metabolomics techniques. Targeted approaches dominated the field, particularly liquid chromatography coupled to a triple quadrupole mass spectrometer, with untargeted methods also receiving significant usage. Applications spanned clinical research, epidemiological studies, clinical diagnostics, patient monitoring, and prognostics across various medical domains, including metabolic diseases, endocrinology, oncology, cardiometabolic risk, neurodegeneration and clinical toxicology. CONCLUSIONS: Despite optimism for the future of clinical metabolomics, challenges such as technical complexity, standardization issues, and financial constraints remain significant hurdles. The study underscores the promising yet intricate landscape of metabolomics in clinical practice, emphasizing the need for continued efforts to overcome barriers and realize its full potential in patient care and precision medicine.
- Keywords
- clinical lipidomics, clinical metabolomics, diagnostics, emerging technologies, laboratory medicine, prognostics,
- MeSH
- Chromatography, Liquid MeSH
- Humans MeSH
- Metabolomics * methods MeSH
- Surveys and Questionnaires MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
Plant specialized metabolites have diversified vastly over the course of plant evolution, and they are considered key players in complex interactions between plants and their environment. The chemical diversity of these metabolites has been widely explored and utilized in agriculture and crop enhancement, the food industry, and drug development, among other areas. However, the immensity of the plant metabolome can make its exploration challenging. Here we describe a protocol for exploring plant specialized metabolites that combines high-resolution mass spectrometry and computational metabolomics strategies, including molecular networking, identification of structural motifs, as well as prediction of chemical structures and metabolite classes.
- Keywords
- GNPS, MS2LDA, MS2Query, MZmine, Molecular networking, Plant metabolomics, SIRIUS, Specialized metabolites,
- MeSH
- Mass Spectrometry * methods MeSH
- Metabolome * MeSH
- Metabolomics * methods MeSH
- Plants * metabolism MeSH
- Computational Biology methods MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Although metabolomics data acquisition and analysis technologies have become increasingly sophisticated over the past 5-10 years, deciphering a metabolite's function from a description of its structure and its abundance in a given experimental setting is still a major scientific and intellectual challenge. To point out ways to address this "data to knowledge" challenge, we developed a functional metabolomics strategy that combines state-of-the-art data analysis tools and applied it to a human scalp metabolomics data set: skin swabs from healthy volunteers with normal or oily scalp (Sebumeter score 60-120, n = 33; Sebumeter score > 120, n = 41) were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS), yielding four metabolomics data sets for reversed phase chromatography (C18) or hydrophilic interaction chromatography (HILIC) separation in electrospray ionization (ESI) + or - ionization mode. Following our data analysis strategy, we were able to obtain increasingly comprehensive structural and functional annotations, by applying the Global Natural Product Social Networking (M. Wang, J. J. Carver, V. V. Phelan, L. M. Sanchez, et al., Nat Biotechnol 34:828-837, 2016, https://doi.org/10.1038/nbt.3597), SIRIUS (K. Dührkop, M. Fleischauer, M. Ludwig, A. A. Aksenov, et al., Nat Methods 16:299-302, 2019, https://doi.org/10.1038/s41592-019-0344-8), and MicrobeMASST (S. ZuffaS, R. Schmid, A. Bauermeister, P. W, P. Gomes, et al., bioRxiv:rs.3.rs-3189768, 2023, https://doi.org/10.21203/rs.3.rs-3189768/v1) tools. We finally combined the metabolomics data with a corresponding metagenomic sequencing data set using MMvec (J. T. Morton, A. A. Aksenov, L. F. Nothias, J. R. Foulds, et. al., Nat Methods 16:1306-1314, 2019, https://doi.org/10.1038/s41592-019-0616-3), gaining insights into the metabolic niche of one of the most prominent microbes on the human skin, Staphylococcus epidermidis.IMPORTANCESystems biology research on host-associated microbiota focuses on two fundamental questions: which microbes are present and how do they interact with each other, their host, and the broader host environment? Metagenomics provides us with a direct answer to the first part of the question: it unveils the microbial inhabitants, e.g., on our skin, and can provide insight into their functional potential. Yet, it falls short in revealing their active role. Metabolomics shows us the chemical composition of the environment in which microbes thrive and the transformation products they produce. In particular, untargeted metabolomics has the potential to observe a diverse set of metabolites and is thus an ideal complement to metagenomics. However, this potential often remains underexplored due to the low annotation rates in MS-based metabolomics and the necessity for multiple experimental chromatographic and mass spectrometric conditions. Beyond detection, prospecting metabolites' functional role in the host/microbiome metabolome requires identifying the biological processes and entities involved in their production and biotransformations. In the present study of the human scalp, we developed a strategy to achieve comprehensive structural and functional annotation of the metabolites in the human scalp environment, thus diving one step deeper into the interpretation of "omics" data. Leveraging a collection of openly accessible software tools and integrating microbiome data as a source of functional metabolite annotations, we finally identified the specific metabolic niche of Staphylococcus epidermidis, one of the key players of the human skin microbiome.
- Keywords
- metabolite annotation, metabolomics, multi-omics integration, scalp, skin microbiome,
- MeSH
- Chromatography, Liquid MeSH
- Humans MeSH
- Metabolomics methods MeSH
- Scalp * MeSH
- Staphylococcus epidermidis * MeSH
- Tandem Mass Spectrometry MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
Microorganisms, plants, and animals alike have specialized acquisition pathways for obtaining metals, with microorganisms and plants biosynthesizing and secreting small molecule natural products called siderophores and metallophores with high affinities and specificities for iron or other non-iron metals, respectively. This chapter details a novel approach to discovering metal-binding molecules, including siderophores and metallophores, from complex samples ranging from microbial supernatants to biological tissue to environmental samples. This approach, called Native Metabolomics, is a mass spectrometry method in which pH adjustment and metal infusion post-liquid chromatography are interfaced with ion identity molecular networking (IIMN). This rule-based data analysis workflow that enables the identification of metal-binding species based on defined mass (m/z) offsets with the same chromatographic profiles and retention times. Ion identity molecular networking connects compounds that are structurally similar by their fragmentation pattern and species that are ion adducts of the same compound by chromatographic shape correlations. This approach has previously revealed new insights into metal binding metabolites, including that yersiniabactin can act as a biological zincophore (in addition to its known role as a siderophore), that the recently elucidated lepotchelin natural products are cyanobacterial metallophores, and that antioxidants in traditional medicine bind iron. Native metabolomics can be conducted on any liquid chromatography-mass spectrometry system to explore the binding of any metal or multiple metals simultaneously, underscoring the potential for this method to become an essential strategy for elucidating biological metal-binding molecules.
- Keywords
- Direct infusion, Metallophore discovery, Native mass spectrometry, Native metabolomics, Natural product discovery, Siderophore discovery,
- MeSH
- Chromatography, Liquid methods MeSH
- Mass Spectrometry * methods MeSH
- Metabolomics * methods MeSH
- Siderophores * metabolism chemistry analysis MeSH
- Iron metabolism analysis MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Siderophores * MeSH
- Iron MeSH
Lipid oxidation is one of the most important processes occurring in living cells and has been investigated through stable end-products. Currently, new insights into many physiological and pathophysiological processes provide a measurement of the first products of oxidation, e.g., oxidized glycerophosphatidylcholines (oxGPCs). Here, we evaluate the capacity of untargeted global metabolomics to measure oxGPCs in serum samples. This evaluation covered analytical reproducibility and data quality as well as the ability to capture metabolic alterations in diverse conditions. The analytical evaluation was performed based on the quality control samples, while the comparative analysis was based on the model of the development of type 2 diabetes mellitus (T2DM). The novelty of this approach arises not only from the measurement of oxGPCs instead of lipid peroxide-derived aldehydes but also from the stratification of the patients according to body mass index (BMI). Such a scenario was dictated by the fact that, despite the well-known relationship between obesity and T2DM development, there are lean individuals suffering from T2DM as well as obese people with normal glucose homeostasis. Our results provided evidence to support the ability of nontargeted metabolomics to measure oxGPCs. Comparative analysis of measured oxGPCs revealed differences in the level of oxGPCs either between different stages of disease development (insulin resistance, prediabetes) or BMI groups (normal weight, overweight, obese). The obtained results provided new insights into the metabolic processes leading to the development of T2DM and opened new paths in the investigation of the impact of body mass in T2DM progress.
- Keywords
- Long chain oxidized glycerophosphatidylcholines, Metabolomics, Oxidation, T2DM, oxGPCs,
- MeSH
- Chromatography, Liquid MeSH
- Diabetes Mellitus, Type 2 blood metabolism MeSH
- Adult MeSH
- Glycerylphosphorylcholine blood chemistry MeSH
- Middle Aged MeSH
- Humans MeSH
- Metabolome physiology MeSH
- Metabolomics methods MeSH
- Oxidation-Reduction MeSH
- Tandem Mass Spectrometry MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Glycerylphosphorylcholine MeSH
Hulled, or ancient, wheats were the earliest domesticated wheats by mankind and the ancestors of current wheats. Their cultivation drastically decreased during the 1960s; however, the increasing demand for a healthy and equilibrated diet led to rediscovering these grains. Our aim was to use a non-targeted metabolomic approach to discriminate and characterize similarities and differences between ancient Triticum varieties. For this purpose, 77 hulled wheat samples from three different varieties were collected: Garfagnana T. turgidum var. dicoccum L. (emmer), ID331 T. monococcum L. (einkorn) and Rouquin T. spelta L. (spelt). The ultra high performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-QTOF) metabolomics approach highlighted a pronounced sample clustering according to the wheat variety, with an excellent predictability (Q²), for all the models built. Fifteen metabolites were tentatively identified based on accurate masses, isotopic pattern, and product ion spectra. Among these, alkylresorcinols (ARs) were found to be significantly higher in spelt and emmer, showing different homologue composition. Furthermore, phosphatidylcholines (PC) and lysophosphatidylcholines (lysoPC) levels were higher in einkorn variety. The results obtained in this study confirmed the importance of ARs as markers to distinguish between Triticum species and revealed their values as cultivar markers, being not affected by the environmental influences.
- Keywords
- foodomics, lipidomics, non-targeted metabolomics, phenolic lipid compounds, small grains,
- MeSH
- Metabolomics methods MeSH
- Triticum classification metabolism MeSH
- Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization MeSH
- Chromatography, High Pressure Liquid MeSH
- Publication type
- Journal Article MeSH
Liquid chromatography with mass spectrometry (LC-MS)-based metabolomics detects thousands of molecular features (retention time-m/z pairs) in biological samples per analysis, yet the metabolite annotation rate remains low, with 90% of signals classified as unknowns. To enhance the metabolite annotation rates, researchers employ tandem mass spectral libraries and challenging in silico fragmentation software. Hydrogen/deuterium exchange mass spectrometry (HDX-MS) may offer an additional layer of structural information in untargeted metabolomics, especially for identifying specific unidentified metabolites that are revealed to be statistically significant. Here, we investigate the potential of hydrophilic interaction liquid chromatography (HILIC)-HDX-MS in untargeted metabolomics. Specifically, we evaluate the effectiveness of two approaches using hypothetical targets: the post-column addition of deuterium oxide (D2O) and the on-column HILIC-HDX-MS method. To illustrate the practical application of HILIC-HDX-MS, we apply this methodology using the in silico fragmentation software MS-FINDER to an unknown compound detected in various biological samples, including plasma, serum, tissues, and feces during HILIC-MS profiling, subsequently identified as N1-acetylspermidine.
- Keywords
- hydrogen/deuterium exchange, liquid chromatography, mass spectrometry, metabolomics, unknown identification,
- MeSH
- Chromatography, Liquid methods MeSH
- Deuterium MeSH
- Hydrophobic and Hydrophilic Interactions MeSH
- Metabolomics * methods MeSH
- Hydrogen Deuterium Exchange-Mass Spectrometry * MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Deuterium MeSH
Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related deaths in the world. HCC is often diagnosed late because patients with early-stage cancer have no apparent symptoms. Therefore, it is desirable to find a reliable method for an early diagnosis based on the detection of metabolites - biomarkers, that can be detected in the early stages of the disease. Untargeted metabolomics is often used as a tool to find a suitable biomarker for several diseases. In this work, untargeted metabolomics was performed on blood plasma samples of HCC patients and compared with healthy individuals and patients with liver cirrhosis. A combination of liquid chromatography and high-resolution mass spectrometry was used as an analytical method. More than a thousand peaks were detected in the blood plasma samples, from which mainly amino acids, carboxylic acids, lipids, and their derivatives were evaluated as potential biomarkers. The data obtained were statistically processed using the analysis of variance, correlation analysis, and principal component analysis.
- Keywords
- Biomarkers, Cirrhosis, Hepatocellular carcinoma, LC-MS, Metabolomics,
- MeSH
- Principal Component Analysis MeSH
- Chromatography, Liquid methods MeSH
- Adult MeSH
- Carcinoma, Hepatocellular * blood MeSH
- Mass Spectrometry methods MeSH
- Liver Cirrhosis blood diagnosis MeSH
- Middle Aged MeSH
- Humans MeSH
- Metabolomics * methods MeSH
- Biomarkers, Tumor * blood MeSH
- Liver Neoplasms * blood MeSH
- Aged MeSH
- Case-Control Studies MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Names of Substances
- Biomarkers, Tumor * MeSH
BACKGROUND: Cryptosporidium is an important gut microbe whose contributions towards infant and immunocompromise patient mortality rates are steadily increasing. Over the last decade, we have seen the development of various tools and methods for studying Cryptosporidium infection and its interactions with their hosts. One area that is sorely overlooked is the effect infection has on host metabolic processes. RESULTS: Using a 1H nuclear magnetic resonance approach to metabolomics, we have explored the nature of the mouse gut metabolome as well as providing the first insight into the metabolome of an infected cell line. Statistical analysis and predictive modelling demonstrated new understandings of the effects of a Cryptosporidium infection, while verifying the presence of known metabolic changes. Of note is the potential contribution of host derived taurine to the diarrhoeal aspects of the disease previously attributed to a solely parasite-based alteration of the gut environment, in addition to other metabolites involved with host cell catabolism. CONCLUSION: This approach will spearhead our understanding of the Cryptosporidium-host metabolic exchange and provide novel targets for tackling this deadly parasite.
- Keywords
- COLO-680N, Cryptosporidiosis, Metabolomics, NMR, Taurine,
- Publication type
- Journal Article MeSH
