Collection and Preparation of Clinical Samples for Metabolomics

The gut metabolome in a cohort of pregnant and lactating women from Antioquia-Colombia

Nutrition during the perinatal period is an essential component of health and one that can severely impact the correct development of a human being and its overall condition, in all the subsequent stages of life. The availability of several compounds, mainly macronutrients and micronutrients, plays a key role in the balanced nutrition of both mother and baby and is a process with direct relation to the gut microbiome. Thus, we hereby refer to the set of small molecules derived from gut microbiome metabolism as the gut metabolome. These continuous processes occurring in the gut of a gestating or lactating mother related to microbial communities and nutrients, can be revealed by metabolomics. In this study, we explore for the first time the gut metabolome of pregnant and lactating women, from our region of Antioquia-Colombia, applying untargeted metabolomics by LC-QTOF-MS, and molecular networking. Regarding the gut metabolome composition of the cohort, we found, key metabolites that can be used as biomarkers of microbiome function, overall metabolic health, dietary intake, pharmacology, and lifestyle. In our cohort, pregnant women evidenced a significantly higher abundance of prostaglandins, alkaloids, corticosteroids, organosilicons, and natural toxins, while in lactating women, lipids stand out. Our results suggest that unveiling the metabolic phenotype of the gut microbiome of an individual, by untargeted metabolomics, allows a broad visualization of the chemical space present in this important niche and enables the recognition of influential indicators of the host's health status and habits, especially of women during this significant perinatal period. This study constitutes the first evidence of the use of untargeted LC-QTOF-MS coupled with molecular networking analysis, of the gut microbiome in a Colombian cohort and establishes a methodology for finding relative abundances of key metabolites, with potential use in nutritional and physiological state assessments, for future personalized health and nutrition practices.

Clinical advances in analytical profiling of signature lipids: implications for severe non-communicable and neurodegenerative diseases

BACKGROUND

Lipids play key roles in numerous biological processes, including energy storage, cell membrane structure, signaling, immune responses, and homeostasis, making lipidomics a vital branch of metabolomics that analyzes and characterizes a wide range of lipid classes. Addressing the complex etiology, age-related risk, progression, inflammation, and research overlap in conditions like Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and Cancer poses significant challenges in the quest for effective therapeutic targets, improved diagnostic markers, and advanced treatments. Mass spectrometry is an indispensable tool in clinical lipidomics, delivering quantitative and structural lipid data, and its integration with technologies like Liquid Chromatography (LC), Magnetic Resonance Imaging (MRI), and few emerging Matrix-Assisted Laser Desorption Ionization- Imaging Mass Spectrometry (MALDI-IMS) along with its incorporation into Tissue Microarray (TMA) represents current advances. These innovations enhance lipidomics assessment, bolster accuracy, and offer insights into lipid subcellular localization, dynamics, and functional roles in disease contexts.

AIM OF THE REVIEW

The review article summarizes recent advancements in lipidomic methodologies from 2019 to 2023 for diagnosing major neurodegenerative diseases, Alzheimer's and Parkinson's, serious non-communicable cardiovascular diseases and cancer, emphasizing the role of lipid level variations, and highlighting the potential of lipidomics data integration with genomics and proteomics to improve disease understanding and innovative prognostic, diagnostic and therapeutic strategies.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Clinical lipidomic studies are a promising approach to track and analyze lipid profiles, revealing their crucial roles in various diseases. This lipid-focused research provides insights into disease mechanisms, biomarker identification, and potential therapeutic targets, advancing our understanding and management of conditions such as Alzheimer's Disease, Parkinson's Disease, Cardiovascular Diseases, and specific cancers.

Alleviation of carbendazim toxicity effect by Moringa oleifera oil and Linum usitatissimum L. oil on testes of male rats: Physiological, histological and in silico study

Carbendazim (CBZ) is a widely used fungicide that is used to control the unwanted growth of fungi on fruits and vegetables. Sixty male rats were divided into six groups, each having ten. Group one served as control, animals belonging to group two were exposed to CBZ in the measure of 200 mg/kg body weight (BW). In the third and fourth groups, rats were administered 800 mg/kg BW of Moringa oleifera (moringa oil) and Linum usitatissimum L. (flaxseed oil), plus CBZ with the same dose given to group two. Groups five and six were administered with moringa and flaxseed oils respectively for six weeks. A marked decline was seen in oxidative stress markers, reduced glutathione (GSH), superoxide dismutase (SOD), catalase (CAT), and a rise in malondialdehyde (MDA) level in group two with severe histological disruptions. Moringa oil and flaxseed oil were used to alleviate these changes. In addition, a biocomputational molecular docking analysis of three proteins found in male rats was performed. In relation to CBZ (CID:10584007) the screened proteins namely testis-expressed protein (TX101_RAT), EPPI_RAT, and glutathione peroxidase 5 (GPX5_RAT) were docked, and their docking score were obtained (-5.9 kcal/mol), (-5.8 kcal/mol) and (-5.6 kcal/mol) respectively. By examining these interactions in 2D and 3D structures, a detailed understanding of the unique and specific binding affinity, hydrogen bonds, hydrophobic interactions, ionic bonds, and water bonds were obtained. Structure-based virtual screening (SBVS) molecular docking analysis showed that protein interaction with CBZ causes reproductive complications in protein expression and functions by hampering their normal function and blocking active sites.

Study on the Characteristics of Traditional Chinese Medicine Syndromes in Patients with Erosive Gastritis Based on Metabolomics

According to traditional Chinese medicine theory, tongue coatings reflect changes in the body. The goal of this study was to identify a metabolite or a set of metabolites capable of classifying characteristics of traditional Chinese medicine syndromes in erosive gastritis. In this study, we collected tongue coatings of patients with erosive gastritis with damp-heat syndrome (DHS), liver depression and qi stagnation syndrome (LDQSS), and healthy volunteers. Then, we analyzed the differences in metabolic characteristics between the two groups based on metabolomics. We identified 14 potential biomarkers related to the DHS group, and six metabolic pathways were enriched. The differential pathways included pyrimidine metabolism, pantothenate and CoA biosynthesis, citrate cycle (TCA cycle), pyruvate metabolism, glycolysis/gluconeogenesis, and purine metabolism. Similarly, in the LDQSS group, we identified 25 potential biomarkers and 18 metabolic pathways were enriched. The top five pathways were the TCA cycle, sphingolipid metabolism, fatty acid biosynthesis, pantothenate and CoA biosynthesis, and the pentose phosphate pathway. In conclusion, the DHS group and the LDQSS group have different characteristics.

Fluid shear stress induces a shift from glycolytic to amino acid pathway in human trophoblasts

BACKGROUND

The human placenta, a tissue with a lifespan limited to the period of pregnancy, is exposed to varying shear rates by maternal blood perfusion depending on the stage of development. In this study, we aimed to investigate the effects of fluidic shear stress on the human trophoblast transcriptome and metabolism.

RESULTS

Based on a trophoblast cell line cultured in a fluidic flow system, changes caused by shear stress were analyzed and compared to static conditions. RNA sequencing and bioinformatics analysis revealed an altered transcriptome and enriched gene ontology terms associated with amino acid and mitochondrial metabolism. A decreased GLUT1 expression and reduced glucose uptake, together with downregulated expression of key glycolytic rate-limiting enzymes, hexokinase 2 and phosphofructokinase 1 was observed. Altered mitochondrial ATP levels and mass spectrometry data, suggested a shift in energy production from glycolysis towards mitochondrial oxidative phosphorylation. This shift in energy production could be supported by increased expression of glutamic-oxaloacetic transaminase variants in response to shear stress as well as under low glucose availability or after silencing of GLUT1. The shift towards amino acid metabolic pathways could be supported by significantly altered amino acid levels, like glutamic acid, cysteine and serine. Downregulation of GLUT1 and glycolytic rate-limiting enzymes, with concomitant upregulation of glutamic-oxaloacetic transaminase 2 was confirmed in first trimester placental explants cultured under fluidic flow. In contrast, high fluid shear stress decreased glutamic-oxaloacetic transaminase 2 expression in term placental explants when compared to low flow rates. Placental tissue from pregnancies with intrauterine growth restriction are exposed to high shear rates and showed also decreased glutamic-oxaloacetic transaminase 2, while GLUT1 was unchanged and glycolytic rate-limiting enzymes showed a trend to be upregulated. The results were generated by using qPCR, immunoblots, quantification of immunofluorescent pictures, padlock probe hybridization, mass spectrometry and FRET-based measurement.

CONCLUSION

Our study suggests that onset of uteroplacental blood flow is accompanied by a shift from a predominant glycolytic- to an alternative amino acid converting metabolism in the villous trophoblast. Rheological changes with excessive fluidic shear stress at the placental surface, may disrupt this alternative amino acid pathway in the syncytiotrophoblast and could contribute to intrauterine growth restriction.

Recent advances in mass spectrometry-based proteomics and metabolomics in chronic rhinosinusitis with nasal polyps

Chronic rhinosinusitis with nasal polyps (CRSwNP) is a complex and heterogeneous disease, typically diagnosed through endoscopy and computed tomography and treated with glucocorticoid or surgery. There is an urgent need to develop molecular-level diagnostic or prognostic tools to better understand the pathophysiology of CRSwNP. Proteomics and metabolomics, emerging fields, offer significant potential in elucidating the mechanisms underlying CRSwNP. Mass spectrometry, a powerful and sensitive tool for trace substance detection, is broadly applied for proteomics and metabolomics analysis in CRSwNP research. While previous literature has summarized the advancement of mass spectrometry-based CRSwNP proteomics from 2004 to 2018, recent years have seen new advances in this field, particularly about non-invasive samples and exosomes. Furthermore, mass spectrometry-based CRSwNP metabolomics research has opened new avenues for inquiry. Therefore, we present a comprehensive review of mass spectrometry-based proteomics and metabolomics studies on CRSwNP conducted between 2019 and 2022. Specifically, we highlight protein and metabolic biomarkers that have been utilized as diagnostic or prognostic markers for CRSwNP. Lastly, we conclude with potential directions for future mass spectrometry-based omics studies of CRSwNP.

Branched-Chain Amino Acids Metabolism and Their Roles in Retinopathy: From Relevance to Mechanism

Retinopathy is one of the leading causes of irreversible blindness and vision loss worldwide. Imbalanced nutrients play important roles in the pathogenesis and pathophysiology of retinal diseases. Branched-Chain Amino Acids (BCAAs), as essential amino acids, perform a variety of biological functions, including protein synthesis, glucose metabolism, lipid metabolism, inflammation, and oxidative stress in metabolic tissues of diabetes and aging-related diseases. Recently, it has been shown that BCAAs are highly related to neuroprotection, oxidative stress, inflammatory and glutamate toxicity in the retina of retinopathy. Therefore, this review summarizes the alterations of BCAA levels in retinopathy, especially diabetic retinopathy and aging-related macular disease, and the genetics, functions, and mechanisms of BCAAs in the retina as well as other metabolic tissues for reference. All of these efforts aim to provide fundamental knowledge of BCAAs for further discoveries and research on retina health based on the sensing and signaling of essential amino acids.

No skin off your back: the sampling and extraction of sebum for metabolomics

INTRODUCTION

Sebum-based metabolomics (a subset of "sebomics") is a developing field that involves the sampling, identification, and quantification of metabolites found in human sebum. Sebum is a lipid-rich oily substance secreted by the sebaceous glands onto the skin surface for skin homeostasis, lubrication, thermoregulation, and environmental protection. Interest in sebomics has grown over the last decade due to its potential for rapid analysis following non-invasive sampling for a range of clinical and environmental applications.

OBJECTIVES

To provide an overview of various sebum sampling techniques with their associated challenges. To evaluate applications of sebum for clinical research, drug monitoring, and human biomonitoring. To provide a commentary of the opportunities of using sebum as a diagnostic biofluid in the future.

METHODS

Bibliometric analyses of selected keywords regarding skin surface analysis using the Scopus search engine from 1960 to 2022 was performed on 12th January 2023. The published literature was compartmentalised based on what the work contributed to in the following areas: the understanding about sebum, its composition, the analytical technologies used, or the purpose of use of sebum. The findings were summarised in this review.

RESULTS

Historically, about 15 methods of sampling have been used for sebum collection. The sample preparation approaches vary depending on the analytes of interest and are summarised. The use of sebum is not limited to just skin diseases or drug monitoring but also demonstrated for other systemic disease. Most of the work carried out for untargeted analysis of metabolites associated with sebum has been in the recent two decades.

CONCLUSION

Sebum has a huge potential beyond skin research and understanding how one's physiological state affects or reflects on the skin metabolome via the sebaceous glands itself or by interactions with sebaceous secretion, will open doors for simpler biomonitoring. Sebum acts as a sink to environmental metabolites and has applications awaiting to be explored, such as biosecurity, cross-border migration, localised exposure to harmful substances, and high-throughput population screening. These applications will be possible with rapid advances in volatile headspace and lipidomics method development as well as the ability of the metabolomics community to annotate unknown species better. A key issue with skin surface analysis that remains unsolved is attributing the source of the metabolites found on the skin surface before meaningful biological interpretation.

Progress of metabolomics in atopic dermatitis: a systematic review

Atopic dermatitis (AD), a chronic inflammatory skin disorder characterized by recurrent eczema and intense pruritus, is a major skin-related burden worldwide. The diagnosis and treatment of AD is often challenging due to the high heterogeneity of AD, and its exact etiology is unknown. Metabolomics offers the opportunity to follow continuous physiological and pathological changes in individuals, which allows accurate diagnosis and management as well as providing deep insights into the etiopathogenesis of AD. Several metabolomic studies of AD have been published over the past few years. The aim of this review is to summarize these findings and help researchers to understand the rapid development of metabolomics for AD. A comprehensive and systematic search was performed using the PubMed, Embase, Cochrane Library and Web of Science databases. Twenty-six papers were finally included in the review after quality assessment. Significant differences in metabolite profiles were found between patients with AD and healthy individuals. This study provides a comprehensive overview of metabolomic research in AD. A better understanding of the metabolomics of AD may offer novel diagnostic, prognostic, and therapeutic approaches.

Current Role of Modern Chromatography with Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy in the Investigation of Biomarkers of Endometriosis

Endometriosis has a wide range of clinical manifestations, and the disease course is unpredictable, making the diagnosis a challenging task. Despite significant advances in the pathophysiology of endometriosis and various proposed theories, the exact etiology is not fully understood and is still unknown. The most commonly used biomarker of endometriosis is CA-125, however, it is nonspecific and is applied for cancers diagnosis. Therefore, the development of reliable noninvasive diagnostic tests for the early diagnosis of endometriosis remains one of the top priorities. Omics technologies are very promising approaches for constructing diagnostic models and biomarker discovery. Their use can greatly facilitate the study of such a complex disease as endometriosis. Nowadays, powerful analytical platforms commonly used in omics, such as gas and liquid chromatography with mass spectrometry and nuclear magnetic resonance (NMR) spectroscopy, have proven to be a promising tools for biomarker discovery. The aim of this review is to summarize the various features of the analytical approaches, practical challenges and features of gas and liquid chromatography with MS and NMR spectroscopy (including sample processing protocols, technological advancements, and methodology) used for profiling of metabolites, lipids, peptides and proteins in physiological fluids and tissues from patients with endometriosis. In addition, this report devotes special attention to the issue of how comprehensive analyses of these profiles can effectively contribute to the study of endometriosis. The search query included reports published between 2012 and 2022 years in PubMed, Web-of-Science, SCOPUS, Science Direct.

Metabolomics as a Critical Tool for Studying Clinical Surgery

Metabolomics enables the analysis of metabolites within an organism, which offers the closest direct measurement of the physiological activity of the organism, and has advanced efforts to characterize metabolic states, identify biomarkers, and investigate metabolic pathways. A high degree of innovation in analytical techniques has promoted the application of metabolomics, especially in the study of clinical surgery. Metabolomics can be employed as a clinical testing method to maximize therapeutic outcomes, and has been applied in rapid diagnosis of diseases, timely postoperative monitoring, prognostic assessment, and personalized medicine. This review focuses on the use of mass spectrometry and nuclear magnetic resonance-based metabolomics in clinical surgery, including identifying metabolic changes before and after surgery, finding disease-associated biomarkers, and exploring the potential of personalized therapy. Challenges and opportunities of metabolomics in organ transplantation are also discussed, with a particular emphasis on metabolomics in donor organ evaluation and protection, prognostic outcome prediction, as well as postoperative adverse reaction monitoring. In the end, current limitations of metabolomics in clinical surgery and future research directions are presented.

Amino Acids Metabolism in Retinopathy: From Clinical and Basic Research Perspective

Retinopathy, including age-related macular degeneration (AMD), diabetic retinopathy (DR), and retinopathy of prematurity (ROP), are the leading cause of blindness among seniors, working-age populations, and children. However, the pathophysiology of retinopathy remains unclear. Accumulating studies demonstrate that amino acid metabolism is associated with retinopathy. This study discusses the characterization of amino acids in DR, AMD, and ROP by metabolomics from clinical and basic research perspectives. The features of amino acids in retinopathy were summarized using a comparative approach based on existing high-throughput metabolomics studies from PubMed. Besides taking up a large proportion, amino acids appear in both human and animal, intraocular and peripheral samples. Among them, some metabolites differ significantly in all three types of retinopathy, including glutamine, glutamate, alanine, and others. Studies on the mechanisms behind retinal cell death caused by glutamate accumulation are on the verge of making some progress. To develop potential therapeutics, it is imperative to understand amino acid-induced retinal functional alterations and the underlying mechanisms. This review delineates the significance of amino acid metabolism in retinopathy and provides possible direction to discover therapeutic targets for retinopathy.

Metabolomics in Diabetic Retinopathy: From Potential Biomarkers to Molecular Basis of Oxidative Stress

Diabetic retinopathy (DR), the leading cause of blindness in working-age adults, is one of the most common complications of diabetes mellitus (DM) featured by metabolic disorders. With the global prevalence of diabetes, the incidence of DR is expected to increase. Prompt detection and the targeting of anti-oxidative stress intervention could effectively reduce visual impairment caused by DR. However, the diagnosis and treatment of DR is often delayed due to the absence of obvious signs of retina imaging. Research progress supports that metabolomics is a powerful tool to discover potential diagnostic biomarkers and therapeutic targets for the causes of oxidative stress through profiling metabolites in diseases, which provides great opportunities for DR with metabolic heterogeneity. Thus, this review summarizes the latest advances in metabolomics in DR, as well as potential diagnostic biomarkers, and predicts molecular targets through the integration of genome-wide association studies (GWAS) with metabolomics. Metabolomics provides potential biomarkers, molecular targets and therapeutic strategies for controlling the progress of DR, especially the interventions at early stages and precise treatments based on individual patient variations.

Metabolomics in Team-Sport Athletes: Current Knowledge, Challenges, and Future Perspectives

Metabolomics is a promising tool for studying exercise physiology and exercise-associated metabolism. It has recently been defined with the term “sportomics” due to metabolomics’ capability to characterize several metabolites in several biological samples simultaneously. This narrative review on exercise metabolomics provides an initial and brief overview of the different metabolomics technologies, sample collection, and further processing steps employed for sport. It also discusses the data analysis and its biological interpretation. Thus, we do not cover sample collection, preparation, and analysis paragraphs in detail here but outline a general outlook to help the reader to understand the metabolomics studies conducted in team-sports athletes, alongside endeavoring to recognize existing or emergent trends and deal with upcoming directions in the field of exercise metabolomics in a team-sports setting.

Genetic Determinants in Airways Obstructive Diseases: The Case of Asthma Chronic Obstructive Pulmonary Disease Overlap

Genome-wide association studies (GWAS) of asthma and chronic obstructive pulmonary disease (COPD) with ever-increasing sample sizes have found multiple genetic loci associated with either disease. However, there are few intersecting loci between asthma and COPD. GWAS specifically focused on asthma-COPD overlap (ACO) have been limited by smaller sample sizes and the lack of a consistent definition of ACO that has also hampered clinical and epidemiologic studies. Other genomic techniques, such as gene expression profiling, are feasible with smaller sample sizes. Genetic analyses of objective measures of airway reactivity and allergy/T2 inflammation biomarkers in COPD studies may be another strategy to overcome limitations in ACO definitions.

Understanding the Significance of Sample Preparation in Studies of the Nanoparticle Metabolite Corona

The adsorption of metabolites to the surface of nanomaterials is a growing area of interest in the field of bionanointeractions. Like its more-established protein counterpart, it is thought that the metabolite corona has a key role in the uptake, distribution, and toxicity of nanomaterials in organisms. Previous research has demonstrated that nanomaterials obtain a unique metabolite fingerprint when exposed to biological matrices; however, there have been some concerns raised over the reproducibility of bionanointeraction research due to challenges in dispersion of nanomaterials and their stability. As such, this work investigates a much-overlooked aspect of this field, i.e., sample preparation, which is vital to the accurate, reproducible, and informative analysis of the metabolite corona. The impact of elution buffer pH, volume, and ionic strength on the metabolite corona composition acquired by uncapped and polyvinylpyrrolidone (PVP)-capped TiO₂ from mixtures of cationic and anionic metabolites was studied. We demonstrate the temporal evolution of the TiO₂ metabolite corona and the recovery of the metabolite corona, which resulted from a complex biological matrix, in this case human plasma. This work also demonstrates that it is vital to optimize sample preparation for each nanomaterial being investigated, as the metabolite recovery from Fe₃O₄ and Dispex-capped TiO₂ nanomaterials is significantly reduced compared to the aforementioned uncapped and PVP-capped TiO₂ nanomaterials. These are important findings for future bionanointeraction studies, which is a rapidly emerging area of research in nanoscience.

Challenges in Metabolomics-Based Tests, Biomarkers Revealed by Metabolomic Analysis, and the Promise of the Application of Metabolomics in Precision Medicine

Metabolomics helps identify metabolites to characterize/refine perturbations of biological pathways in living organisms. Pre-analytical, analytical, and post-analytical limitations that have hampered a wide implementation of metabolomics have been addressed. Several potential biomarkers originating from current targeted metabolomics-based approaches have been discovered. Precision medicine argues for algorithms to classify individuals based on susceptibility to disease, and/or by response to specific treatments. It also argues for a prevention-based health system. Because of its ability to explore gene-environment interactions, metabolomics is expected to be critical to personalize diagnosis and treatment. Stringent guidelines have been applied from the very beginning to design studies to acquire the information currently employed in precision medicine and precision prevention approaches. Large, prospective, expensive and time-consuming studies are now mandatory to validate old, and discover new, metabolomics-based biomarkers with high chances of translation into precision medicine. Metabolites from studies on saliva, sweat, breath, semen, feces, amniotic, cerebrospinal, and broncho-alveolar fluid are predicted to be needed to refine information from plasma and serum metabolome. In addition, a multi-omics data analysis system is predicted to be needed for omics-based precision medicine approaches. Omics-based approaches for the progress of precision medicine and prevention are expected to raise ethical issues.

An evaluation of the National Institutes of Health grants portfolio: identifying opportunities and challenges for multi-omics research that leverage metabolomics data

BACKGROUND

Through the systematic large-scale profiling of metabolites, metabolomics provides a tool for biomarker discovery and improving disease monitoring, diagnosis, prognosis, and treatment response, as well as for delineating disease mechanisms and etiology. As a downstream product of the genome and epigenome, transcriptome, and proteome activity, the metabolome can be considered as being the most proximal correlate to the phenotype. Integration of metabolomics data with other -omics data in multi-omics analyses has the potential to advance understanding of human disease development and treatment.

AIM OF REVIEW

To understand the current funding and potential research opportunities for when metabolomics is used in human multi-omics studies, we cross-sectionally evaluated National Institutes of Health (NIH)-funded grants to examine the use of metabolomics data when collected with at least one other -omics data type. First, we aimed to determine what types of multi-omics studies included metabolomics data collection. Then, we looked at those multi-omics studies to examine how often grants employed an integrative analysis approach using metabolomics data.

KEY SCIENTIFIC CONCEPTS OF REVIEW

We observed that the majority of NIH-funded multi-omics studies that include metabolomics data performed integration, but to a limited extent, with integration primarily incorporating only one other -omics data type. Some opportunities to improve data integration may include increasing confidence in metabolite identification, as well as addressing variability between -omics approach requirements and -omics data incompatibility.

Development and Application of an LC-MS/MS Untargeted Exposomics Method with a Separated Pooled Quality Control Strategy

Pooled quality controls (QCs) are usually implemented within untargeted methods to improve the quality of datasets by removing features either not detected or not reproducible. However, this approach can be limiting in exposomics studies conducted on groups of exposed and nonexposed subjects, as compounds present at low levels only in exposed subjects can be diluted and thus not detected in the pooled QC. The aim of this work is to develop and apply an untargeted workflow for human biomonitoring in urine samples, implementing a novel separated approach for preparing pooled quality controls. An LC-MS/MS workflow was developed and applied to a case study of smoking and non-smoking subjects. Three different pooled quality controls were prepared: mixing an aliquot from every sample (QC-T), only from non-smokers (QC-NS), and only from smokers (QC-S). The feature tables were filtered using QC-T (T-feature list), QC-S, and QC-NS, separately. The last two feature lists were merged (SNS-feature list). A higher number of features was obtained with the SNS-feature list than the T-feature list, resulting in identification of a higher number of biologically significant compounds. The separated pooled QC strategy implemented can improve the nontargeted human biomonitoring for groups of exposed and nonexposed subjects.

Recent Advances in Understanding of Alzheimer's Disease Progression through Mass Spectrometry-Based Metabolomics

Alzheimer's disease (AD) is the leading cause of dementia in the aging population, but despite extensive research, there is no consensus on the biological cause of AD. While AD research is dominated by protein/peptide-centric research based on the amyloid hypothesis, a theory that designates dysfunction in beta-amyloid production, accumulation, or disposal as the primary cause of AD, many studies focus on metabolomics as a means of understanding the biological processes behind AD progression. In this review, we discuss mass spectrometry (MS)-based AD metabolomics studies, including sample type and preparation, mass spectrometry specifications, and data analysis, as well as biological insights gleaned from these studies, with the hope of informing future AD metabolomic studies.

Defining Blood Plasma and Serum Metabolome by GC-MS

Metabolomics uses advanced analytical chemistry methods to analyze metabolites in biological samples. The most intensively studied samples are blood and its liquid components: plasma and serum. Armed with advanced equipment and progressive software solutions, the scientific community has shown that small molecules’ roles in living systems are not limited to traditional “building blocks” or “just fuel” for cellular energy. As a result, the conclusions based on studying the metabolome are finding practical reflection in molecular medicine and a better understanding of fundamental biochemical processes in living systems. This review is not a detailed protocol of metabolomic analysis. However, it should support the reader with information about the achievements in the whole process of metabolic exploration of human plasma and serum using mass spectrometry combined with gas chromatography.

Metabolomics Insights into Inflammatory Bowel Disease: A Comprehensive Review

Inflammatory bowel disease (IBD) is a chronic, complex relapsing disorder characterised by immune dysregulation, gut microbiota alteration, and disturbed intestinal permeability. The diagnosis and the management of IBD are challenging due to the recurrent nature and complex evolution of the disease. Furthermore, the molecular mechanism underlying the aetiology and pathogenesis of IBD is still poorly understood. There is an unmet need for novel, reliable, and noninvasive tools for diagnosing and monitoring IBD. In addition, metabolomic profiles may provide a priori determination of optimal therapeutics and reveal novel targets for therapies. This review tries to gather scientific evidence to summarise the emerging contribution of metabolomics to elucidate the mechanisms underlying IBD and changes associated with disease phenotype and therapies, as well as to identify biomarkers with metabolic imbalance in those patients. Metabolite changes during health and disease could provide insights into the disease pathogenesis and the discovery of novel indicators for the diagnosis and prognosis assessment of IBD. Metabolomic studies in IBD have shown changes in tricarboxylic acid cycle intermediates, amino-acid and fatty-acid metabolism, and oxidative pathways. Metabolomics has made progress towards identifying metabolic alterations that may provide clinically useful biomarkers and a deeper understanding of the disease. However, at present, there is insufficient evidence evaluating the predictive accuracy of these molecular signatures and their diagnostic ability, which is necessary before metabolomic data can be translated into clinical practice.

Chorioamnionitis alters lung surfactant lipidome in newborns with respiratory distress syndrome

BACKGROUND

Chorioamnionitis is associated with preterm delivery and morbidities; its role in lung disease is controversial. The aim of this study is to assess the effect of chorioamnionitis on metabolite and lipid profiles of epithelial lining fluid in preterm newborns with respiratory distress syndrome (RDS).

METHODS

The study involved 30 newborns with RDS, born from mothers with or without histological chorioamnionitis (HCA): HCA+, N = 10; HCA-, N = 20. Patients had a gestational age ≤30 weeks; the groups were matched for age and birth weights. Tracheal aspirates were collected within 24 h after birth and analyzed using liquid chromatography/mass spectrometry-based untargeted lipidomics.

RESULTS

According to Mann-Whitney U tests, 570 metabolite features had statistically significantly higher or lower concentrations (p < 0.05) in tracheal aspirates of HCA+ compared to HCA-, and 241 metabolite features were putatively annotated and classified. The most relevant changes involved higher levels of glycerophospholipids (fold change 2.42-17.69) and sphingolipids, with lower concentration of all annotated sphingomyelins in HCA+ (fold change 0.01-0.50).

CONCLUSIONS

Untargeted lipidomics of tracheal aspirates suggested the production of lipid mediators in the context of an ongoing inflammatory status in HCA+ babies. However, the effect of chorioamnionitis on epithelial lining fluid composition deserves further investigations on a larger group of infants.

IMPACT

Our lipidomics investigation on tracheal aspirates of preterm newborns at birth suggested that exposure to maternal histological chorioamnionitis may cause changes in epithelial lining fluid composition. This is the first description of epithelial lining fluid lipidomic profiles in preterm infants with and without exposition to chorioamnionitis. These results could provide novel link between placental membrane inflammation and newborns' respiratory outcome.

Liquid Chromatography-Mass Spectrometry for Clinical Metabolomics: An Overview

Metabolomics is a discipline that offers a comprehensive analysis of metabolites in biological samples. In the last decades, the notable evolution in liquid chromatography and mass spectrometry technologies has driven an exponential progress in LC-MS-based metabolomics. Targeted and untargeted metabolomics strategies are important tools in health and medical science, especially in the study of disease-related biomarkers, drug discovery and development, toxicology, diet, physical exercise, and precision medicine. Clinical and biological problems can now be understood in terms of metabolic phenotyping. This overview highlights the current approaches to LC-MS-based metabolomics analysis and its applications in the clinical research.

Toxicometabolomics: Small Molecules to Answer Big Toxicological Questions

Given the high biological impact of classical and emerging toxicants, a sensitive and comprehensive assessment of the hazards and risks of these substances to organisms is urgently needed. In this sense, toxicometabolomics emerged as a new and growing field in life sciences, which use metabolomics to provide new sets of susceptibility, exposure, and/or effects biomarkers; and to characterize in detail the metabolic responses and altered biological pathways that various stressful stimuli cause in many organisms. The present review focuses on the analytical platforms and the typical workflow employed in toxicometabolomic studies, and gives an overview of recent exploratory research that applied metabolomics in various areas of toxicology.

Identification of potential serum metabolic biomarkers for patient with keratoconus using untargeted metabolomics approach

This study aimed to investigate the metabolite differences between patients with keratoconus and control subjects and identify potential serum biomarkers for keratoconus using a non-targeted metabolomics approach. Venous blood samples were obtained from patients with keratoconus (n = 20) as well as from age-, gender- and race-matched control subjects (n = 20). Metabolites extracted from serum were separated and analyzed by liquid chromatography/quadrupole time-of-flight mass spectrometer. Processing of raw data and analysis of the data files was performed using Agilent Mass Hunter Qualitative software. The identified metabolites were subjected to a principal component and hierarchical cluster analysis. Appropriate statistical tests were used to analyze the metabolomic profiling data. Together, the analysis revealed that the dehydroepiandrosterone sulfate from the steroidal hormone synthesis pathway was significantly upregulated in patients with keratoconus (p < 0.05). Also, a combination of eicosanoids from the arachidonic acid pathway, mainly prostaglandin F2α, prostaglandin A2, 16,16-dimethyl prostaglandin E2, and 5-hydroxyeicosatetraenoic acid were collectively up-regulated as a group in keratoconus patients (p < 0.05). On the other hand, glycerophospholipid PS(17:2(9Z,12Z)/20:4(5Z,8Z,11Z,14Z)) was found to be significantly upregulated in the metabolomics profiles of control subjects (p < 0.05). The differently regulated metabolites provide insights into the pathophysiology of keratoconus and could potentially be used as biomarkers for keratoconus to aid in screening for individuals at risk hence, enabling early diagnosis and timely monitoring of disease.

Mass spectrometry based high-throughput bioanalysis of low molecular weight compounds: are we ready to support personalized medicine?

Liquid chromatography coupled to mass spectrometry (LC-MS) is the gold standard in bioanalysis for the development of quantitative assays to support drug development or therapeutic drug monitoring. High-throughput and low-cost gene sequencing have enabled a paradigm shift from one treatment fits all to personalized medicine (PM). However, gene monitoring provides only partial information about the health state. The full picture requires the combination of gene monitoring with the screening of exogenous compounds, metabolites, lipids, and proteins. This critical review discusses how mass spectrometry–based technologies and approaches including separation sciences, ambient ionization, and ion mobility are/could be used to support high-throughput bioanalysis of endogenous end exogenous low molecular weight compounds. It includes also various biological sample types (from blood to expired air), and various sample preparation techniques.

Cerebrospinal fluid metabolomics: detection of neuroinflammation in human central nervous system disease

The high morbidity and mortality of neuroinflammatory diseases drives significant interest in understanding the underlying mechanisms involved in the innate and adaptive immune response of the central nervous system (CNS). Diagnostic biomarkers are important to define treatable neuroinflammation. Metabolomics is a rapidly evolving research area offering novel insights into metabolic pathways, and elucidation of reliable metabolites as biomarkers for diseases. This review focuses on the emerging literature regarding the detection of neuroinflammation using cerebrospinal fluid (CSF) metabolomics in human cohort studies. Studies of classic neuroinflammatory disorders such as encephalitis, CNS infection and multiple sclerosis confirm the utility of CSF metabolomics. Additionally, studies in neurodegeneration and neuropsychiatry support the emerging potential of CSF metabolomics to detect neuroinflammation in common CNS diseases such as Alzheimer's disease and depression. We demonstrate metabolites in the tryptophan-kynurenine pathway, nitric oxide pathway, neopterin and major lipid species show moderately consistent ability to differentiate patients with neuroinflammation from controls. Integration of CSF metabolomics into clinical practice is warranted to improve recognition and treatment of neuroinflammation.

Aircraft noise exposure drives the activation of white blood cells and induces microvascular dysfunction in mice

Epidemiological studies showed that traffic noise has a dose-dependent association with increased cardiovascular morbidity and mortality. Whether microvascular dysfunction contributes significantly to the cardiovascular health effects by noise exposure remains to be established. The connection of inflammation and immune cell interaction with microvascular damage and functional impairment is also not well characterized. Male C57BL/6J mice or gp91phox^−/y mice with genetic deletion of the phagocytic NADPH oxidase catalytic subunit (gp91phox or NOX-2) were used at the age of 8 weeks, randomly instrumented with dorsal skinfold chambers and exposed or not exposed to aircraft noise for 4 days. Proteomic analysis (using mass spectrometry) revealed a pro-inflammatory phenotype induced by noise exposure that was less pronounced in noise-exposed gp91phox^−/y mice. Using in vivo fluorescence microscopy, we found a higher number of adhesive leukocytes in noise-exposed wild type mice. Dorsal microvascular diameter (by trend), red blood cell velocity, and segmental blood flow were also decreased by noise exposure indicating microvascular constriction. All adverse effects on functional parameters were normalized or improved at least by trend in noise-exposed gp91phox^−/y mice. Noise exposure also induced endothelial dysfunction in cerebral microvessels, which was associated with higher oxidative stress burden and inflammation, as measured using video microscopy. We here establish a link between a pro-inflammatory phenotype of plasma, activation of circulating leukocytes and microvascular dysfunction in mice exposed to aircraft noise. The phagocytic NADPH oxidase was identified as a central player in the underlying pathophysiological mechanisms.

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Noise exposure induces a pro-thrombo-inflammatory phenotype in mouse plasma.

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Aircraft noise increases leukocyte-endothelium interactions in dorsal microvessels.

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Noise decreases segmental blood flow/red blood cell velocity in dorsal microvessels.

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Noise increases cerebral microvascular dysfunction and oxidative stress.

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Nox2 deficiency (gp91phox^-/y) improves noise-induced adverse effects.

Application of Lipid Class Ratios for Sample Stability Monitoring-Evaluation of Murine Tissue Homogenates and SDS as a Stabilizer

Lipids are a ubiquitous class of structurally complex molecules involved in various biological processes. In the fast-growing field of lipidomics, preanalytical issues are frequently neglected. Here, we investigated the stability of lipid profiles of murine liver, brain, lung, heart, and spleen homogenates by quantitative flow injection analysis using tandem mass spectrometry and high-resolution mass spectrometry. Storage of tissue homogenates at room temperature showed substantial alterations of the lipid profiles reflecting lipolytic action. Therefore, ratios of ceramide to sphingomyelin, lysophosphatidylethanolamine to phosphatidylethanolamine, lysophosphatidylcholine to phosphatidylcholine, and diglyceride to triglyceride were applied to monitor sample stability and the effect of sodium dodecyl sulfate (SDS) as a potential stabilizing agent. The addition of SDS led to a concentration-dependent stabilization of lipid profiles in liver, brain, and heart homogenates, while in lung and spleen homogenates, in particular, the lysophosphatidylethanolamine to phosphatidylethanolamine ratio increased upon addition of SDS. In conclusion, we demonstrated that lipid class ratios reflecting lipolytic activity could be applied to evaluate both the stability of samples and the influence of stabilizers.

Metabolomic-based clinical studies and murine models for acute pancreatitis disease: A review

Acute pancreatitis (AP) is one of the most common gastroenterological disorders requiring hospitalization and is associated with substantial morbidity and mortality. Metabolomics nowadays not only help us to understand cellular metabolism to a degree that was not previously obtainable, but also to reveal the importance of the metabolites in physiological control, disease onset and development. An in-depth understanding of metabolic phenotyping would be therefore crucial for accurate diagnosis, prognosis and precise treatment of AP. In this review, we summarized and addressed the metabolomics design and workflow in AP studies, as well as the results and analysis of the in-depth of research. Based on the metabolic profiling work in both clinical populations and experimental AP models, we described the metabolites with potential utility as biomarkers and the correlation between the altered metabolites and AP status. Moreover, the disturbed metabolic pathways correlated with biological function were discussed in the end. A practical understanding of current and emerging metabolomic approaches applicable to AP and use of the metabolite information presented will aid in designing robust metabolomics and biological experiments that result in identification of unique biomarkers and mechanisms, and ultimately enhanced clinical decision-making.

Metabolomics: The Stethoscope for the Twenty-First Century

Metabolomics encompasses the systematic identification and quantification of all metabolic products in the human body. This field could provide clinicians with novel sets of diagnostic biomarkers for disease states in addition to quantifying treatment response to medications at an individualized level. This literature review aims to highlight the technology underpinning metabolic profiling, identify potential applications of metabolomics in clinical practice, and discuss the translational challenges that the field faces. We searched PubMed, MEDLINE, and EMBASE for primary and secondary research articles regarding clinical applications of metabolomics. Metabolic profiling can be performed using mass spectrometry and nuclear magnetic resonance-based techniques using a variety of biological samples. This is carried out in vivo or in vitro following careful sample collection, preparation, and analysis. The potential clinical applications constitute disruptive innovations in their respective specialities, particularly oncology and metabolic medicine. Outstanding issues currently preventing widespread clinical use are scalability of data interpretation, standardization of sample handling practice, and e-infrastructure. Routine utilization of metabolomics at a patient and population level will constitute an integral part of future healthcare provision.

Mass spectrometry-based determination of lipids and small molecules composing adipose tissue with a focus on brown adipose tissue

Adipose tissue has been the subject of research for a very long time. Many studies perform a comprehensive analysis of different types of adipose tissue with an emphasis on brown adipose tissue. Mass spectrometry-based approaches are particularly useful in the exploration not only of the metabolic composition of adipose tissue but also its function. In the presented review, a complex and critical overview of publications devoted to the analysis of adipose tissue by means of mass spectrometry was performed. Detailed investigation of analytical aspects related to either untargeted or targeted analysis of adipose tissue was performed, leading to the formation of a collection of hints at the available analytical methods. Moreover, a profound analysis of the metabolic composition of brown adipose tissue was performed. Brown adipose tissue metabolome was characterized on structural and functional levels, providing information about its exact metabolic composition but also connecting these molecules and placing them into biochemical pathways. All our work resulted in a very broad picture of the analysis of adipose tissue, starting from the analytical aspects and finishing on the current knowledge about its composition.

A review of strategies for untargeted urinary metabolomic analysis using gas chromatography-mass spectrometry

BACKGROUND

Human urine gives evidence of the metabolism in the body and contains different metabolites at various concentrations. A number of analytical techniques including mass spectrometry (MS) and nuclear magnetic resonance (NMR) have been used to obtain metabolites levels in urine samples. However, gas chromatography-mass spectrometry (GC-MS) is one of the most widely used techniques for urinary metabolomics studies due to its higher sensitivity, resolution, reproducibility, reliability, relatively low cost and ease of operation compared to liquid chromatography-mass spectrometry and NMR.

AIM OF REVIEW

This review looks at various aspects of urine preparation prior to analysis by GC-MS including sample storage, urease pretreatment, derivatization, use of internal standard and quality control samples for data correction. In addition, most common types of inlet liners, ionization techniques and columns are discussed and a summary of mass analyzers are also highlighted. Lastly, the role of retention index in metabolite identification and data normalization methods are presented.

KEY SCIENTIFIC CONCEPTS OF REVIEW

The purpose of this review is summarizing methods of sample storage, pretreatment, and GC-MS analysis that are mostly used in urine metabolomics studies. Specific emphasis is given to the critical steps within the GC-MS urine metabolomics that those new to this field need to be aware of and the remaining challenges that require further attention and studies.

Implementation of liquid chromatography-high resolution mass spectrometry methods for untargeted metabolomic analyses of biological samples: A tutorial

Untargeted metabolomics is now widely recognized as a useful tool for exploring metabolic changes taking place in biological systems under different conditions. By its nature, this is a highly interdisciplinary field of research, and mastering all of the steps comprised in the pipeline can be a challenging task, especially for those researchers new to the topic. In this tutorial, we aim to provide an overview of the most widely adopted methods of performing LC-HRMS-based untargeted metabolomics of biological samples. A detailed protocol is provided in the Supplementary Information for rapidly implementing a basic screening workflow in a laboratory setting. This tutorial covers experimental design, sample preparation and analysis, signal processing and data treatment, and, finally, data analysis and its biological interpretation. Each section is accompanied by up-to-date literature to guide readers through the preparation and optimization of such a workflow, as well as practical information for avoiding or fixing some of the most frequently encountered pitfalls.

From Samples to Insights into Metabolism: Uncovering Biologically Relevant Information in LC-HRMS Metabolomics Data

Untargeted metabolomics (including lipidomics) is a holistic approach to biomarker discovery and mechanistic insights into disease onset and progression, and response to intervention. Each step of the analytical and statistical pipeline is crucial for the generation of high-quality, robust data. Metabolite identification remains the bottleneck in these studies; therefore, confidence in the data produced is paramount in order to maximize the biological output. Here, we outline the key steps of the metabolomics workflow and provide details on important parameters and considerations. Studies should be designed carefully to ensure appropriate statistical power and adequate controls. Subsequent sample handling and preparation should avoid the introduction of bias, which can significantly affect downstream data interpretation. It is not possible to cover the entire metabolome with a single platform; therefore, the analytical platform should reflect the biological sample under investigation and the question(s) under consideration. The large, complex datasets produced need to be pre-processed in order to extract meaningful information. Finally, the most time-consuming steps are metabolite identification, as well as metabolic pathway and network analysis. Here we discuss some widely used tools and the pitfalls of each step of the workflow, with the ultimate aim of guiding the reader towards the most efficient pipeline for their metabolomics studies.

Application of GC/MS-Based Metabonomic Profiling in Studying the Therapeutic Effects of Aconitum carmichaeli with Ampelopsis japonica Extract on Collagen-Induced Arthritis in Rats

Aconitum carmichaeli with Ampelopsis japonica (AA) is a classical traditional Chinese medicine (TCM) formula. There are a lot of examples showing that AA can be used to treat rheumatoid arthritis, but its mechanism of action is still not completely clear. In this research, collagen-induced arthritis (CIA) was chosen as a rheumatoid arthritis (RA) model. Rats of treated groups were continuously administered Aconitum carmichaeli (AC), Ampelopsis japonica (AJ) and Aconitum carmichaeli + Ampelopsis japonica (AA) orally once a day from the day after the onset of arthritis (day 7) until day 42. The results showed that AA not only significantly reduced paw swelling, but also improved the levels of TNF-α and IL-6 in serum. GC-MS-based urine metabonomics was established to analysis metabolic profiles and 21 biomarkers of RA rats were identified by the Partial Least Squares Discriminant Analysis (PLS-DA) and Support Vector Machine (SVM) methods. The prediction rate of the SVM method for the 21 biomarkers was 100%. Twenty of 21 biomarkers, including D-galactose, inositol and glycerol, gradually returned to normal levels after administration of AA. Metabolomic Pathway Analysis (MetPA) generated three related metabolic pathways-galactose metabolism, glycerolipid metabolism and inositol phosphate metabolism-which explain the mechanism of AA treatment of rheumatoid arthritis. This research provides a better understanding of the therapeutic effects and possible therapeutic mechanism of action of a complex TCM (AA) on rheumatoid arthritis.

Metabolomics in the study of retinal health and disease

Metabolomics is the qualitative and quantitative assessment of the metabolites (small molecules < 1.5 kDa) in body fluids. The metabolites are the downstream of the genetic transcription and translation processes and also downstream of the interactions with environmental exposures; thus, they are thought to closely relate to the phenotype, especially for multifactorial diseases. In the last decade, metabolomics has been increasingly used to identify biomarkers in disease, and it is currently recognized as a very powerful tool with great potential for clinical translation. The metabolome and the associated pathways also help improve our understanding of the pathophysiology and mechanisms of disease. While there has been increasing interest and research in metabolomics of the eye, the application of metabolomics to retinal diseases has been limited, even though these are leading causes of blindness. In this manuscript, we perform a comprehensive summary of the tools and knowledge required to perform a metabolomics study, and we highlight essential statistical methods for rigorous study design and data analysis. We review available protocols, summarize the best approaches, and address the current unmet need for information on collection and processing of tissues and biofluids that can be used for metabolomics of retinal diseases. Additionally, we critically analyze recent work in this field, both in animal models and in human clinical disease, including diabetic retinopathy and age-related macular degeneration. Finally, we identify opportunities for future research applying metabolomics to improve our current assessment and understanding of mechanisms of vitreoretinal diseases, and to hence improve patient assessment and care.

Metabolomics in chronic kidney disease: Strategies for extended metabolome coverage

Chronic kidney disease (CKD) is becoming a major public health issue as prevalence is increasing worldwide. It also represents a major challenge for the identification of new early biomarkers, understanding of biochemical mechanisms, patient monitoring and prognosis. Each metabolite contained in a biofluid or tissue may play a role as a signal or as a driver in the development or progression of the pathology. Therefore, metabolomics is a highly valuable approach in this clinical context. It aims to provide a representative picture of a biological system, making exhaustive metabolite coverage crucial. Two aspects can be considered: analytical and biological coverage. From an analytical point of view, monitoring all metabolites within one run is currently impossible. Multiple analytical techniques providing orthogonal information should be carried out in parallel for coverage improvement. The biological aspect of metabolome coverage can be enhanced by using multiple biofluids or tissues for in-depth biological investigation, as the analysis of a single sample type is generally insufficient for whole organism extrapolation. Hence, recording of signals from multiple sample types and different analytical platforms generates massive and complex datasets so that chemometric tools, including data fusion approaches and multi-block analysis, are key tools for extracting biological information and for discovery of relevant biomarkers. This review presents the recent developments in the field of metabolomic analysis, from sampling and analytical strategies to chemometric tools, dedicated to the generation and handling of multiple complementary metabolomic datasets enabling extended metabolite coverage to improve our biological knowledge of CKD.

Advances in metabolome information retrieval: turning chemistry into biology. Part I: analytical chemistry of the metabolome

Metabolites are small molecules produced by enzymatic reactions in a given organism. Metabolomics or metabolic phenotyping is a well-established omics aimed at comprehensively assessing metabolites in biological systems. These comprehensive analyses use analytical platforms, mainly nuclear magnetic resonance spectroscopy and mass spectrometry, along with associated separation methods to gather qualitative and quantitative data. Metabolomics holistically evaluates biological systems in an unbiased, data-driven approach that may ultimately support generation of hypotheses. The approach inherently allows the molecular characterization of a biological sample with regard to both internal (genetics) and environmental (exosome, microbiome) influences. Metabolomics workflows are based on whether the investigator knows a priori what kind of metabolites to assess. Thus, a targeted metabolomics approach is defined as a quantitative analysis (absolute concentrations are determined) or a semiquantitative analysis (relative intensities are determined) of a set of metabolites that are possibly linked to common chemical classes or a selected metabolic pathway. An untargeted metabolomics approach is a semiquantitative analysis of the largest possible number of metabolites contained in a biological sample. This is part I of a review intending to give an overview of the state of the art of major metabolic phenotyping technologies. Furthermore, their inherent analytical advantages and limits regarding experimental design, sample handling, standardization and workflow challenges are discussed.