Mass spectrometry-based holistic analytical approaches for metabolite profiling in systems biology studies

Metabolic Patterns of Fluconazole Resistant and Susceptible Candida auris Clade V and I

Candida auris, an emerging non-albicans multidrug-resistant yeast, has become a significant cause of invasive candidiasis in healthcare settings. So far, data on the metabolites of C. auris in different clades are minimal, and no studies have focused on clade V metabolites. Therefore, Gas chromatography-mass spectrometry (GC-MS) was used for the metabolomic profiling of clade I C. auris compared with fluconazole-resistant and susceptible C. auris in clade V strains. GC-MS chromatography revealed 28, 22, and 30 compounds in methanolic extracts of the fluconazole-susceptible and fluconazole-resistant C. auris clade V and C. auris clade I strain, respectively. Some compounds, such as acetamide and metaraminol, were found in fluconazole-susceptible and resistant C. auris clade V and clade I. N-methyl-ethanamine and bis(2-ethylhexyl) phthalate metabolites were found in both fluconazole -susceptible and resistant C. auris clade V, as well as 3-methyl-4-isopropylphenol, 3,5-bis(1,1-dimethyl)-1,2-benzenediol, and diisostyl phthalate metabolites in both fluconazole resistant C. auris clade V and I. Identifying these metabolites contributes to understanding the morphogenesis and pathogenesis of C. auris, highlighting their potential role in antifungal drug resistance and the control of fungal growth. However, further experiments are warranted to fully comprehend the identified metabolites' regulatory responses, and there may be potential challenges in translating these findings into clinical applications.

A critical appraisal of the role of metabolomics in breast cancer research and diagnostics

Breast cancer (BC) remains the most prevalent cancer among women worldwide, despite significant advancements in its prevention and treatment. The escalating incidence of BC globally necessitates continued research into novel diagnostic and therapeutic strategies. Metabolomics, a burgeoning field, offers a comprehensive analysis of all metabolites within a cell, tissue, system, or organism, providing crucial insights into the dynamic changes occurring during cancer development and progression. This review focuses on the metabolic alterations associated with BC, highlighting the potential of metabolomics in identifying biomarkers for early detection, diagnosis, treatment and prognosis. Metabolomics studies have revealed distinct metabolic signatures in BC, including alterations in lipid metabolism, amino acid metabolism, and energy metabolism. These metabolic changes not only support the rapid proliferation of cancer cells but also influence the tumour microenvironment and therapeutic response. Furthermore, metabolomics holds great promise in personalized medicine, facilitating the development of tailored treatment strategies based on an individual's metabolic profile. By providing a holistic view of the metabolic changes in BC, metabolomics has the potential to revolutionize our understanding of the disease and improve patient outcomes.

Metabolic biomarkers in irritable bowel syndrome diagnosis

Irritable bowel syndrome (IBS) is a chronic gastrointestinal (GI) disorder characterized by altered bowel habits and abdominal discomfort during defecation. It significantly impacts life quality and work productivity for those affected. Global data suggests a slightly higher prevalence in females than in males. Today, unambiguous diagnosis of IBS remains challenging due to the absence of a specific biochemical, histopathological, or radiological test. Current diagnosis relies heavily on thorough symptom evaluation. Efforts by the Rome committees have established standardized diagnostic criteria (Rome I-IV), improving consistency and clinical applicability. Recent studies in this framework, seem to have successfully employed metabolomics techniques to identify distinct metabolite profiles in breath and stool samples of IBS patients, differentiating them from healthy controls and those with other functional GI disorders, such as inflammatory bowel disease (IBD). Building on this success, researchers are investigating the presence of similar metabolites in easily accessible biofluids such as urine, potentially offering a less invasive diagnostic approach. Accordingly, this review focuses on key metabolites specifically detected in IBS patients' biological specimens, with a focus on urinary metabolites, using various methods, particularly mass spectrometry (MS)-based techniques, including gas chromatography-MS (GC-MS), liquid chromatography-tandem MS (LC-MS/MS), and capillary electrophoresis-MS (CE-MS) metabolomics assays. These findings may make provision for a new set of non-invasive biomarkers for IBS diagnosis and management.

Metabolomic Changes in Rat Serum after Chronic Exposure to Glyphosate-Based Herbicide

Glyphosate-based herbicides (GBHs) have gained extensive popularity in recent decades. For many years, glyphosate has been regarded as harmless or minimally toxic to mammals due to the absence of its primary target, the shikimic acid pathway in humans. Nonetheless, mounting evidence suggests that glyphosate may cause adverse health effects in humans via other mechanisms. In this study, we described the metabolomic changes in the serum of experimental rats exposed to chronic GBH using the highly sensitive LC-MS/MS technique. We investigated the possible relationship between chronic exposure to GBH and neurological disorders. Our findings suggest that chronic exposure to GBH can alter spatial learning memory and the expression of some important metabolites that are linked to neurophysiological disorders in young rats, with the female rats showing higher susceptibility compared to the males. This indicates that female rats are more likely to show early symptoms of the disorder on exposure to chronic GBH compared to male rats. We observed that four important metabolites (paraxanthine, epinephrine, L-(+)-arginine, and D-arginine) showed significant changes and involvement in neurological changes as suggested by ingenuity pathway analysis. In conclusion, our results indicate that chronic exposure to GBH can increase the risk of developing neurological disorders.

Simultaneously quantifying hundreds of acylcarnitines in multiple biological matrices within ten minutes using ultrahigh-performance liquid-chromatography and tandem mass spectrometry

Acylcarnitines are metabolic intermediates of fatty acids and branched-chain amino acids having vital biofunctions and pathophysiological significances. Here, we developed a high-throughput method for quantifying hundreds of acylcarnitines in one run using ultrahigh performance liquid chromatography and tandem mass spectrometry (UPLC-MS/MS). This enabled simultaneous quantification of 1136 acylcarnitines (C0-C26) within 10-min with good sensitivity (limit of detection < 0.7 fmol), linearity (correlation coefficient > 0.992), accuracy (relative error < 20%), precision (coefficient of variation (CV), CV < 15%), stability (CV < 15%), and inter-technician consistency (CV < 20%, n = 6). We also established a quantitative structure-retention relationship (goodness of fit > 0.998) for predicting retention time (tR) of acylcarnitines with no standards and built a database of their multiple reaction monitoring parameters (tR, ion-pairs, and collision energy). Furthermore, we quantified 514 acylcarnitines in human plasma and urine, mouse kidney, liver, heart, lung, and muscle. This provides a rapid method for quantifying acylcarnitines in multiple biological matrices.

Diverse forage improves lipid metabolism and antioxidant capacity in goats, as revealed by metabolomics

It is well established that promoting the balance of nutrients and plant secondary metabolites (PSM) by feeding diverse forage physiologically improves ruminant production. However, the underlying mechanism remains unclear. To investigate the physiological mechanism related to the improvement of physiological stress tolerance, ruminants were fed diverse forage. Oxidative stress markers were quantified, and serum metabolomics was performed. Six crossbred Shiba wethers (32.8 ± 9.2 kg BW) were arranged in a replicated 3 × 3 Latin square design. The treatments were feeding only Sudan grass hay (100% SDN); feeding a mixture of Sudan grass and alfalfa hay (70:30, SDN-ALF); and feeding a mixture of Sudan grass, timothy grass, and alfalfa hay (35:35:30; SDN-TMT-ALF). Each diet group was fed its specific diet for 21 days with a 14-day adaptation period. Feed intake and digestibility, blood biochemistry, total antioxidant capacity (TAC), and superoxide dismutase (SOD) were analysed. In addition, blood serum metabolites were assessed by liquid chromatography-tandem mass spectrometry. The DM intake and DM, organic matter, and CP digestibility were higher (P < 0.05) in the SDN-TMT-ALF group than in the SDN group. The TAC was higher (P < 0.01) in the SDN-TMT-ALF and SDN-ALF groups (809.51 and 813.7 µM, respectively) than the SDN group (720.69 µM), while the SOD level was unchanged (P = 0.06) among the treatments. Total serum cholesterol and NH3 levels were higher (P < 0.05) in the SDN-TMT-ALF group (89.17 mg/dL and 242.42 µg/dL, respectively) than in the SDN group (71.00 mg/dL and 89.17 µg/dL). Additionally, the levels of nine metabolites in serum differed among the treatments (P < 0.05). Linoleic acid (LA) and cortisone, which are related to LA metabolism and the steroid biosynthesis pathway, were upregulated by the SDN-ALF and SDN-TMT-ALF diets compared to the SDN diet, suggesting the contribution of ALF to altering the metabolites. The levels of hippuric acid, which is a metabolite of phenolic compounds, were higher (P < 0.001) in the animals fed SDN, which contained higher phenolic and luteolin concentrations than the other diets. Pathway analysis suggested that the higher cortisone levels were derived from cholesterol due to upregulated glycolysis metabolism, which was positively related to increased ingestion, digestibility, and serum LA levels in animals given mixed forage. In conclusion, physiological stress tolerance in the animals was regulated by upregulation of LA and steroid hormone metabolism, which was associated with an increase in TAC rather than the ability of the animal to regulate its PSM intake.

Mass spectrometry-based approaches to assess the botanical authenticity of dietary supplements

Dietary supplements are legally considered foods despite frequently including medicinal plants as ingredients. Currently, the consumption of herbal dietary supplements, also known as plant food supplements (PFS), is increasing worldwide and some raw botanicals, highly demanded due to their popularity, extensive use, and/or well-established pharmacological effects, have been attaining high prices in the international markets. Therefore, botanical adulteration for profit increase can occur along the whole PFS industry chain, from raw botanicals to plant extracts, until final PFS. Besides the substitution of high-value species, unintentional mislabeling can happen in morphologically similar species. Both cases represent a health risk for consumers, prompting the development of numerous works to access botanical adulterations in PFS. Among different approaches proposed for this purpose, mass spectrometry (MS)-based techniques have often been reported as the most promising, particularly when hyphenated with chromatographic techniques. Thus, this review aims at describing an overview of the developments in this field, focusing on the applications of MS-based techniques to targeted and untargeted analysis to detect botanical adulterations in plant materials, extracts, and PFS.

Metabolomics: A useful tool for ischemic stroke research

Ischemic stroke (IS) is a multifactorial and heterogeneous disease. Despite years of studies, effective strategies for the diagnosis, management and treatment of stroke are still lacking in clinical practice. Metabolomics is a growing field in systems biology. It is starting to show promise in the identification of biomarkers and in the use of pharmacometabolomics to help patients with certain disorders choose their course of treatment. The development of metabolomics has enabled further and more biological applications. Particularly, metabolomics is increasingly being used to diagnose diseases, discover new drug targets, elucidate mechanisms, and monitor therapeutic outcomes and its potential effect on precision medicine. In this review, we reviewed some recent advances in the study of metabolomics as well as how metabolomics might be used to identify novel biomarkers and understand the mechanisms of IS. Then, the use of metabolomics approaches to investigate the molecular processes and active ingredients of Chinese herbal formulations with anti-IS capabilities is summarized. We finally summarized recent developments in single cell metabolomics for exploring the metabolic profiles of single cells. Although the field is relatively young, the development of single cell metabolomics promises to provide a powerful tool for unraveling the pathogenesis of IS.

Quality Control in Targeted GC-MS for Amino Acid-OMICS

Gas chromatography-mass spectrometry (GC-MS) is suitable for the analysis of non-polar analytes. Free amino acids (AA) are polar, zwitterionic, non-volatile and thermally labile analytes. Chemical derivatization of AA is indispensable for their measurement by GC-MS. Specific conversion of AA to their unlabeled methyl esters (d0Me) using 2 M HCl in methanol (CH3OH) is a suitable derivatization procedure (60 min, 80 °C). Performance of this reaction in 2 M HCl in tetradeutero-methanol (CD3OD) generates deuterated methyl esters (d3Me) of AA, which can be used as internal standards in GC-MS. d0Me-AA and d3Me-AA require subsequent conversion to their pentafluoropropionyl (PFP) derivatives for GC-MS analysis using pentafluoropropionic anhydride (PFPA) in ethyl acetate (30 min, 65 °C). d0Me-AA-PFP and d3Me-AA-PFP derivatives of AA are readily extractable into water-immiscible, GC-compatible organic solvents such as toluene. d0Me-AA-PFP and d3Me-AA-PFP derivatives are stable in toluene extracts for several weeks, thus enabling high throughput quantitative measurement of biological AA by GC-MS using in situ prepared d3Me-AA as internal standards in OMICS format. Here, we describe the development of a novel OMICS-compatible QC system and demonstrate its utility for the quality control of quantitative analysis of 21 free AA and metabolites in human plasma samples by GC-MS as Me-PFP derivatives. The QC system involves cross-standardization of the concentrations of the AA in their aqueous solutions at four concentration levels and a quantitative control of AA at the same four concentration levels in pooled human plasma samples. The retention time (tR)-based isotope effects (IE) and the difference (δ(H/D) of the retention times of the d0Me-AA-PFP derivatives (tR(H)) and the d3Me-AA-PFP derivatives (tR(D)) were determined in study human plasma samples of a nutritional study (n = 353) and in co-processed QC human plasma samples (n = 64). In total, more than 400 plasma samples were measured in eight runs in seven working days performed by a single person. The proposed QC system provides information about the quantitative performance of the GC-MS analysis of AA in human plasma. IE, δ(H/D) and a massive drop of the peak area values of the d3Me-AA-PFP derivatives may be suitable as additional parameters of qualitative analysis in targeted GC-MS amino acid-OMICS.

Integrative metabolomics science in Alzheimer's disease: Relevance and future perspectives

Alzheimer's disease (AD) is determined by various pathophysiological mechanisms starting 10-25 years before the onset of clinical symptoms. As multiple functionally interconnected molecular/cellular pathways appear disrupted in AD, the exploitation of high-throughput unbiased omics sciences is critical to elucidating the precise pathogenesis of AD. Among different omics, metabolomics is a fast-growing discipline allowing for the simultaneous detection and quantification of hundreds/thousands of perturbed metabolites in tissues or biofluids, reproducing the fluctuations of multiple networks affected by a disease. Here, we seek to critically depict the main metabolomics methodologies with the aim of identifying new potential AD biomarkers and further elucidating AD pathophysiological mechanisms. From a systems biology perspective, as metabolic alterations can occur before the development of clinical signs, metabolomics - coupled with existing accessible biomarkers used for AD screening and diagnosis - can support early disease diagnosis and help develop individualized treatment plans. Presently, the majority of metabolomic analyses emphasized that lipid metabolism is the most consistently altered pathway in AD pathogenesis. The possibility that metabolomics may reveal crucial steps in AD pathogenesis is undermined by the difficulty in discriminating between the causal or epiphenomenal or compensatory nature of metabolic findings.

Metabolomic Profiling in Children with Celiac Disease: Beyond the Gluten-Free Diet

Celiac disease (CD) is included in the group of complex or multifactorial diseases, i.e., those caused by the interaction of genetic and environmental factors. Despite a growing understanding of the pathophysiological mechanisms of the disease, diagnosis is still often delayed and there are no effective biomarkers for early diagnosis. The only current treatment, a gluten-free diet (GFD), can alleviate symptoms and restore intestinal villi, but its cellular effects remain poorly understood. To gain a comprehensive understanding of CD's progression, it is crucial to advance knowledge across various scientific disciplines and explore what transpires after disease onset. Metabolomics studies hold particular significance in unravelling the complexities of multifactorial and multisystemic disorders, where environmental factors play a significant role in disease manifestation and progression. By analyzing metabolites, we can gain insights into the reasons behind CD's occurrence, as well as better comprehend the impact of treatment initiation on patients. In this review, we present a collection of articles that showcase the latest breakthroughs in the field of metabolomics in pediatric CD, with the aim of trying to identify CD biomarkers for both early diagnosis and treatment monitoring. These advancements shed light on the potential of metabolomic analysis in enhancing our understanding of the disease and improving diagnostic and therapeutic strategies. More studies need to be designed to cover metabolic profiles in subjects at risk of developing the disease, as well as those analyzing biomarkers for follow-up treatment with a GFD.

To metabolomics and beyond: a technological portfolio to investigate cancer metabolism

Tumour cells have exquisite flexibility in reprogramming their metabolism in order to support tumour initiation, progression, metastasis and resistance to therapies. These reprogrammed activities include a complete rewiring of the bioenergetic, biosynthetic and redox status to sustain the increased energetic demand of the cells. Over the last decades, the cancer metabolism field has seen an explosion of new biochemical technologies giving more tools than ever before to navigate this complexity. Within a cell or a tissue, the metabolites constitute the direct signature of the molecular phenotype and thus their profiling has concrete clinical applications in oncology. Metabolomics and fluxomics, are key technological approaches that mainly revolutionized the field enabling researchers to have both a qualitative and mechanistic model of the biochemical activities in cancer. Furthermore, the upgrade from bulk to single-cell analysis technologies provided unprecedented opportunity to investigate cancer biology at cellular resolution allowing an in depth quantitative analysis of complex and heterogenous diseases. More recently, the advent of functional genomic screening allowed the identification of molecular pathways, cellular processes, biomarkers and novel therapeutic targets that in concert with other technologies allow patient stratification and identification of new treatment regimens. This review is intended to be a guide for researchers to cancer metabolism, highlighting current and emerging technologies, emphasizing advantages, disadvantages and applications with the potential of leading the development of innovative anti-cancer therapies.

Modified glucose as a sensor to track the metabolism of individual living endothelial cells - Observation of the 1602 cm−1 band called “Raman spectroscopic signature of life”

A relatively new approach to subcellular research is Raman microscopy with the application of sensors called Raman probes. This paper describes the use of the sensitive and specific Raman probe, 3-O-propargyl-d-glucose (3-OPG), to track metabolic changes in endothelial cells (ECs). ECs play a significant role in a healthy and dysfunctional state, the latter is correlated with a range of lifestyle diseases, particularly with cardiovascular disorders. The metabolism and glucose uptake may reflect the physiopathological conditions and cell activity correlated with energy utilization. To study metabolic changes at the subcellular level the glucose analogue, 3-OPG was used, which shows a characteristic and intense Raman band at 2124 cm^-1.3-OPG was applied as a sensor to track both, its accumulation in live and fixed ECs and then metabolism in normal and inflamed ECs, by employing two spectroscopic techniques, i.e. spontaneous and stimulated Raman scattering microscopies. The results indicate that 3-OPG is a sensitive sensor to follow glucose metabolism, manifested by the Raman band of 1602 cm^-1. The 1602 cm^-1 band has been called the "Raman spectroscopic signature of life" in the cell literature, and here we demonstrate that it is attributed to glucose metabolites. Additionally, we have shown that glucose metabolism and its uptake are slowed down in the cellular inflammation. We showed that Raman spectroscopy can be classified as metabolomics, and its uniqueness lies in the fact that it allows the analysis of the processes of a single living cell. Gaining further knowledge on metabolic changes in the endothelium, especially in pathological conditions, may help in identifying markers of cellular dysfunction, and more broadly in cell phenotyping, better understanding of the mechanism of disease development and searching for new treatments.

Increased Serum Sodium at Acute Kidney Injury Onset Predicts In-Hospital Death

Background

Over the last decades, acute kidney injury (AKI) has been identified as a potentially fatal diagnosis which substantially increases in-hospital mortality in the short term and morbidity/mortality in the long term. However, reliable biomarkers for predicting AKI-associated outcomes are still missing. In this study, we assessed whether serum sodium, measured at different time points during the in-hospital treatment period, provided prognostic information in AKI.

Methods

This was a retrospective, observational cohort study. AKI subjects were identified via the in-hospital AKI alert system. Serum sodium and potassium levels were documented at five pre-defined time points: hospital admission, AKI onset, minimum estimated glomerular filtration rate, minimum and maximum of the respective electrolyte during the treatment period. In-hospital death, the need for kidney replacement therapy (KRT) and recovery of kidney function were defined as endpoints.

Results

Patients who suffered in-hospital death (n = 37, 23.1%) showed significantly higher serum sodium levels at diagnosis of AKI (survivors: 145.7 ± 2.13 vs. non-survivors: 138.8 ± 0.636 mmol/L, P = 0.003). A logistic regression model was significant for serum sodium levels in patients with in-hospital death (X², P = 0.003; odds ratio = 1.08 (1.022 - 1.141); R² = 0.082; d = 0.089). This suggests an increase of the relative risk for in-hospital death by 8% with every unit of serum sodium increase. Patients with a sodium above the upper normal range at AKI diagnosis were also more likely to suffer in-hospital death (P = 0.001).

Conclusion

In summary, we present evidence that serum sodium, measured at time of AKI diagnosis, potentially serves as a predictor for in-hospital death in patients with AKI.

Data Processing and Analysis in Mass Spectrometry-Based Metabolomics

Metabolomics is the latest of the omics sciences. It attempts to measure and characterize metabolites-small chemical compounds <1500 Da-on cells, tissue, or biofluids, which are usually products of biological reactions. As metabolic reactions are closer to the phenotype, metabolomics has emerged as an attractive science for various areas of research, including personalized medicine. However, due to the complexity of data obtained and the absence of curated databases for metabolite identification, data processing is the major bottleneck in this area since most technicians lack the required bioinformatics expertise to process datasets in a reliable and fast manner. The aim of this chapter is to describe the available tools for data processing that makes an inexperienced researcher capable of obtaining reliable results without having to undergo through huge parametrization steps.

Untargeted Metabolomics Pilot Study Using UHPLC-qTOF MS Profile in Sows' Urine Reveals Metabolites of Bladder Inflammation

Urinary tract infections (UTI) of sows (characterized by ascending infections of the urinary bladder (cyst), ureters, and renal pelvis), are major health issues with a significant economic impact to the swine industry. The current detection of UTI incidents lacks sensitivity; thus, UTIs remain largely under-diagnosed. The value of metabolomics in unraveling the mechanisms of sow UTI has not yet been established. This study aims to investigate the urine metabolome of sows for UTI biomarkers. Urine samples were collected from 58 culled sows from a farrow-to-finish herd in Greece. Urine metabolomic profiles in 31 healthy controls and in 27 inflammatory ones were evaluated. UHPLC-qTOF MS/MS was applied for the analysis with a combination of multivariate and univariate statistical analysis. Eighteen potential markers were found. The changes in several urine metabolites classes (nucleosides, indoles, isoflavones, and dipeptides), as well as amino-acids allowed for an adequate discrimination between the study groups. Identified metabolites were involved in purine metabolism; phenylalanine; tyrosine and tryptophan biosynthesis; and phenylalanine metabolism. Through ROC analysis it was shown that the 18 identified metabolite biomarkers exhibited good predictive accuracy. In summary, our study provided new information on the potential targets for predicting early and accurate diagnosis of UTI. Further, this information also sheds light on how it could be applied in live animals.

Metabolomic- and Molecular Networking-Based Exploration of the Chemical Responses Induced in Citrus sinensis Leaves Inoculated with Xanthomonas citri

Citrus canker, caused by the bacterium Xanthomonas citri subsp. citri (X. citri), is a plant disease affecting Citrus crops worldwide. However, little is known about defense compounds in Citrus. Here, we conducted a mass spectrometry-based metabolomic approach to obtain an overview of the chemical responses of Citrus leaves to X. citri infection. To facilitate result interpretation, the multivariate analyses were combined with molecular networking to identify biomarkers. Metabolite variations among untreated and X. citri-inoculated Citrus samples under greenhouse conditions highlighted induced defense biomarkers. Notably, the plant tryptophan metabolism pathway was activated, leading to the accumulation of N-methylated tryptamine derivatives. This finding was subsequently confirmed in symptomatic leaves in the field. Several tryptamine derivatives showed inhibitory effects in vitro against X. citri. This approach has enabled the identification of new chemically related biomarker groups and their dynamics in the response of Citrus leaves to Xanthomonas infection.

UHPLC-MS/MS method for the simultaneous determination of nicotine and tobacco-specific nitrosamines NNN and NNK for use in preclinical studies

A new method was developed and validated for the simultaneous determination of nicotine and tobacco-specific nitrosamines (TSNAs) 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) and N-nitrosonornicotine (NNN) in two different tests matrices: porcine buccal epithelium tissue and phosphate buffered saline (PBS) extracts of smokeless tobacco products. The novelty of this work is in the development of a liquid chromatography tandem mass spectrometry method that can provide simultaneous quantification of trace levels of TSNAs and high concentrations of nicotine in biological media. Precision, accuracy, and stability were evaluated during method validation to ensure the method was fit for purpose. Several sample preparation and extraction methods were evaluated to minimize matrix effects and maximize analyte recoveries. The method was accurate in the range of 81.1% - 117%; repeatability was estimated in the range of 1.5% - 13.6% across multiple concentrations. The linear regression correlation coefficient (R2) was greater than 0.9959 for all analytes, and the limit of detection (LOD) was determined for nicotine, NNK, and NNN at 1 ng/mL 0.005 ng/mL, and 0.006 ng/ mL, respectively. Our method was found to be appropriate for the analysis of nicotine, NNN, and NNK in the porcine buccal epithelium and PBS extracts of smokeless tobacco products.

Guide to Metabolomics Analysis: A Bioinformatics Workflow

Metabolomics is an emerging field that quantifies numerous metabolites systematically. The key purpose of metabolomics is to identify the metabolites corresponding to each biological phenotype, and then provide an analysis of the mechanisms involved. Although metabolomics is important to understand the involved biological phenomena, the approach's ability to obtain an exhaustive description of the processes is limited. Thus, an analysis-integrated metabolomics, transcriptomics, proteomics, and other omics approach is recommended. Such integration of different omics data requires specialized statistical and bioinformatics software. This review focuses on the steps involved in metabolomics research and summarizes several main tools for metabolomics analyses. We also outline the most abnormal metabolic pathways in several cancers and diseases, and discuss the importance of multi-omics integration algorithms. Overall, our goal is to summarize the current metabolomics analysis workflow and its main analysis software to provide useful insights for researchers to establish a preferable pipeline of metabolomics or multi-omics analysis.

A metabolomics strategy to identify potential biomarkers associated with human laryngeal cancer based on dried blood spot mass spectrometry approach

ABSTRACT

Laryngeal cancer (LC) as one of common malignant tumors in the head and neck region accounted for 1% to 5% of new cancer cases and was ranked as the third otolaryngology cancer. However, some patients with LC were diagnosed at the advanced stage, which can cause delayed diagnosis and treatment. It is an urgent task to seek effective biomarkers for the early diagnosis of LC aimed at alleviating suffering.A combination of dried blood spot sampling and direct infusion mass spectrometry technology was applied to 39 patients with LC and 53 healthy individuals. Multiple algorithms towards 93 metabolites including amino acids and carnitine/acylcarnitines were run for selecting differential metabolites. Furthermore, leave-one-out cross-validation method was used to evaluate diagnostic performance of selected metabolite biomarkers.A biomarker panel consisting of arginine, proline, hexacosanoic carnitine, ornithine /citrulline, and 3-hydroxy-octadecenoylcarnitine exhibited potential to distinguish patients with LC from healthy individuals, with a sensitivity of 0.8974 and a specificity of 0.8302 in leave-one-out cross-validation model.The metabolomic analysis of LC patients is beneficial to screen disease-associated biomarkers and develop new diagnostic approaches.

Thermal degradation of metabolites in urine using multiple isotope-labelled internal standards for off-line GC metabolomics - effects of injector and oven temperatures

Thermal processes are widely used in small molecule chemical analysis and metabolomics for derivatization, vaporization, chromatography, and ionization, especially in gas chromatography mass spectrometry (GC/MS). An optimized derivatization protocol has been successfully applied using multiple isotope labelled analytical internal standards of selected deuterated and ¹³C selected compounds, covering a range of different groups of metabolites for non-automated GC metabolomics (off-line). Moreover, the study was also realized in a pooled urine sample, following metabolic profiling. A study of thermal degradation of metabolites due to GC inlet and oven programs (fast, slow) was performed, where the results indicated that both GC oven programs (fast and slow) negatively affected the thermal stability of the metabolites, while the fast-ramp GC program also suppressed MS signals. However, the use of multiple internal standards can overcome this drawback. The application of extended temperature ramp GC program presented identical behaviour on metabolite stability and better chromatographic separation combined with much lower signal suppression, compared to a short temperature ramp program. No effects were observed for organic acids, fatty acids, sugars and sugar alcohols, while significant differences were observed for amino acids. GC metabolomics is a strong tool that can facilitate analysis, but special attention is required for sampling handling and heating, before and during the GC analysis. The use and application of multiple multi-group internal standards is highly recommended.

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

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

Effects of Bisphenol A and Bisphenol S Exposure at Low Doses on the Metabolome of Adolescent Male Sprague-Dawley Rats

Toxic effects induced upon exposure to low-dose bisphenol A (BPA) or bisphenol S (BPS) remains controversial. In this study, metabolomics was used to examine the metabolomic perturbation arising from 28 days of exposure to BPA or BPS at 50 μg/kg bw/day in Sprague-Dawley (SD) rats. Endogenous metabolite profiling revealed a clear discrimination of metabolome in the rat plasma among BPA-treatment, BPS-treatment, and control groups. BPA exposure induced the up-regulation of 19 metabolites and down-regulation of 32 metabolites in plasma of SD rats, compared with the control. BPS exposure induced the up-regulation of 15 metabolites and the down-regulation of 33 metabolites in the plasma of SD rats, compared with the control. Joint pathway analysis suggested marked perturbations in the citrate cycle, butanoate metabolism, and alanine, aspartate, and glutamate metabolism for BPA-exposed rats as well as glycerophospholipid metabolism for BPS-exposed rats. These findings provide novel insights into associations between the metabolomic perturbation and phenotypic changes arising from BPA and BPS exposure.

UPLC-MS-Based Serum Metabolomics Reveals Potential Biomarkers of Ang II-Induced Hypertension in Mice

Hypertension is caused by polygenic inheritance and the interaction of various environmental factors. Abnormal function of the renin-angiotensin-aldosterone system (RAAS) is closely associated with changes in blood pressure. As an essential factor in the RAAS, angiotensin II (Ang II) contributes to vasoconstriction and inflammatory responses. However, the effects of overproduction of Ang II on the whole body-metabolism have been unclear. In this study, we established a hypertensive mouse model by micro-osmotic pump perfusion of Ang II, and the maximum systolic blood pressure reached 140 mmHg after 2 weeks. By ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry, the metabolites in the serum of hypertensive model and control mice were analyzed. Partial least squares discriminant analysis (PLS-DA) in both positive and negative ionization modes showed clear separation of the two groups. Perfusion of Ang II induced perturbations of multiple metabolic pathways in mice, such as steroid hormone biosynthesis and galactose metabolism. Tandem mass spectrometry revealed 40 metabolite markers with potential diagnostic value for hypertension. Our data indicate that non-targeted metabolomics can reveal biochemical pathways associated with Ang II-induced hypertension. Although researches about the clinical use of these metabolites as potential biomarkers in hypertension is still needed, the current study improves the understanding of systemic metabolic response to sustained release of Ang II in hypertensive mice, providing a new panel of biomarkers that may be used to predict blood pressure fluctuations in the early stages of hypertension.

Exploring metabolic alterations associated with death from asphyxia and the differentiation of asphyxia from sudden cardiac death by GC-HRMS-based untargeted metabolomics

The determination of cause of death is one of the most important tasks in forensic practice. However, asphyxia is a difficult cause of death to determine, especially when the deceased has an underlying disease that can lead to a sudden unexpected death, such as coronary atherosclerotic heart disease (CAHD, which is the leading cause of sudden cardiac death, SCD), because its determination is currently still based on an exclusion strategy. In this study, gas chromatography coupled with high-resolution mass spectrometry (GC-HRMS)-based untargeted metabolomics was employed to obtain the pulmonary metabolic profiles of rats who died from asphyxia and SCD. First, fourteen metabolites were identified to investigate the mechanism of death from asphyxia, and we proposed some explanations that may account for these metabolic alterations, including the perturbation of amino acid metabolism, lipid metabolism, and energy metabolism (TCA cycle). Second, we discovered eight potential biomarkers to differentiate between asphyxia and SCD as the cause of death. The excellent classification performances of the eight individual biomarkers and their combination in fresh lung tissue were observed. Third, we also explored the relative change in the concentration of the eight metabolites and their classification performance in decomposed tissue (at 24 h postmortem). Lactic acid, pantothenic acid, and the combination of the eight biomarkers can be recognized as perfect classifiers to discriminate asphyxia from SCD even when decomposition has occurred. Our results showed that GC-HRMS-based untargeted metabolomics can be used as a promising tool to explore the metabolic alterations of the death process and to determine the cause of death.

The Use of Gas Chromatography Coupled with High-Resolution Mass Spectrometry-Based Untargeted Metabolomics to Discover Metabolic Changes and Help in the Determination of Complex Causes of Death: A Preliminary Study

The determination of cause of death (COD) is one of the most important tasks in forensic practice and is mainly based on macroscopical and microscopical morphological signatures. However, some CODs are hard to determine because the significant morphological signatures can be nonspecific, variable, subjective, or even absent in the real world. In this study, gas chromatography coupled with high-resolution mass spectrometry (GC-HRMS)-based untargeted metabolomics was employed to obtain plasma metabolic profiles of rats that died from anaphylactic shock (AS), mechanical asphyxia (MA), or sudden cardiac death (SCD). The metabolic alterations of each COD group compared to the control group were investigated using a principal component analysis, partial least-squares discriminant analysis, the Wilcoxon test, and fold change analysis. A range of differential features was screened, and 11, 8, and 7 differential metabolites were finally verified for the AS, MA, and SCD groups, respectively. We proposed some explanations that may account for these metabolic differences, including glucose metabolism, the tricarboxylic acid cycle, glycolysis, lipid metabolism, creatinine catabolism, and purine metabolism. Next, for each COD, we used its differential metabolites, which were obtained through comparisons of each COD group to the control group and represented the metabolic changes of the individual COD, to perform a receiver operating characteristic (ROC) analysis to preliminarily evaluate their ability to discriminate each COD group from the other COD groups. We found that creatinine in the AS group and malic acid and uric acid in the MA group might represent some specific metabolic changes for the relevant COD with high areas under the curve in the ROC curve analysis. Moreover, the combination panel for AS or MA also showed a good ability to discriminate it from the others. However, SCD had fewer metabolic signatures and was relatively harder to discriminate from the other CODs in our work. The preliminary study demonstrates the feasibility of GC-HRMS-based untargeted metabolomics as a promising tool to reveal metabolic changes in different death processes and to determine the complex CODs.

STRATEGIES AND CHALLENGES IN METHOD DEVELOPMENT AND VALIDATION FOR THE ABSOLUTE QUANTIFICATION OF ENDOGENOUS BIOMARKER METABOLITES USING LIQUID CHROMATOGRAPHY-TANDEM MASS SPECTROMETRY

Metabolomics is a dynamically evolving field, with a major application in identifying biomarkers for drug development and personalized medicine. Numerous metabolomic studies have identified endogenous metabolites that, in principle, are eligible for translation to clinical practice. However, few metabolomic-derived biomarker candidates have been qualified by regulatory bodies for clinical applications. Such interruption in the biomarker qualification process can be largely attributed to various reasons including inappropriate study design and inadequate data to support the clinical utility of the biomarkers. In addition, the lack of robust assays for the routine quantification of candidate biomarkers has been suggested as a potential bottleneck in the biomarker qualification process. In fact, the nature of the endogenous metabolites precludes the application of the current validation guidelines for bioanalytical methods. As a result, there have been individual efforts in modifying existing guidelines and/or developing alternative approaches to facilitate method validation. In this review, three main challenges for method development and validation for endogenous metabolites are discussed, namely matrix effects evaluation, alternative analyte-free matrices, and the choice of internal standards (ISs). Some studies have modified the equations described by the European Medicines Agency for the evaluation of matrix effects. However, alternative strategies were also described; for instance, calibration curves can be generated in solvents and in biological samples and the slopes can be compared through ratios, relative standard deviation, or a modified Stufour suggested approaches while quantifying mainly endogenous metabolitesdent t-test. ISs, on the contrary, are diverse; in which seven different possible types, used in metabolomics-based studies, were identified in the literature. Each type has its advantages and limitations; however, isotope-labeled ISs and ISs created through isotope derivatization show superior performance. Finally, alternative matrices have been described and tested during method development and validation for the quantification of endogenous entities. These alternatives are discussed in detail, highlighting their advantages and shortcomings. The goal of this review is to compare, apprise, and debate current knowledge and practices in order to aid researchers and clinical scientists in developing robust assays needed during the qualification process of candidate metabolite biomarkers. © 2019 John Wiley & Sons Ltd. Mass Spec Rev.

Lipidomic UPLC-MS/MS Profiles of Normal-Appearing White Matter Differentiate Primary and Secondary Progressive Multiple Sclerosis

Multiple sclerosis (MS) is a neurodegenerative inflammatory disease where an autoimmune response to components of the central nervous system leads to a loss of myelin and subsequent neurological deterioration. People with MS can develop primary or secondary progressive disease (PPMS, SPMS) and differentiation of the specific differences in the pathogenesis of these two courses, at the molecular level, is currently unclear. Recently, lipidomics studies using human biofluids, mainly plasma and cerebrospinal fluid, have highlighted a possible role for lipids in the initiation and progression of MS. However, there is a lack of lipidomics studies in MS on CNS tissues, such as normal-appearing white matter (NAWM), where local inflammation initially occurs. Herein, we developed an untargeted reverse phase ultra-performance liquid chromatography time of flight tandem mass spectrometry (RP-UPLC-TOF MS^E)-based workflow, in combination with multivariate and univariate statistical analysis, to assess significant differences in lipid profiles in brain NAWM from post-mortem cases of PPMS, SPMS and controls. Groups of eight control, nine PPMS and seven SPMS NAWM samples were used. Correlation analysis of the identified lipids by RP-UPLC-TOF MS^E was undertaken to remove those lipids that correlated with age, gender and post-mortem interval as confounding factors. We demonstrate that there is a significantly altered lipid profile of control cases compared with MS cases and that progressive disease, PPMS and SPMS, can be differentiated on the basis of the lipidome of NAWM with good sensitivity, specificity and prediction accuracy based on receiver operating characteristic (ROC) curve analysis. Metabolic pathway analysis revealed that the most altered lipid pathways between PPMS and SPMS were glycerophospholipid metabolism, glycerophosphatidyl inositol (GPI) anchor synthesis and linoleic acid metabolism. Further understanding of the impact of these lipid alterations described herein associated with progression will provide an increased understanding of the mechanisms underpinning progression and highlight possible new therapeutic targets.

Thrombin-based discovery strategy of bioactive-chemical quality marker combination for pollen of Typha orientalis by metabolomics coupled with chemometrics

BACKGROUND

It is of utmost significance to choose the bioactive components as quality markers for ensuring the effectiveness of traditional Chinese medicine (TCM). Nonetheless, some markers are able to assess effectively the quality of TCM without considering the pharmacological mechanisms and intrinsic chemical complexities.

OBJECTIVE

This underscores the need to discover new and efficient markers which can assess both quality and mechanism of action. Herein, a strategy of bioactive-chemical quality marker combination was proposed to improve the level of the quality control of TCM by metabolomics coupled with chemometrics.

METHODS

A four-step plan was followed. Firstly, acquisition of metabolic features and component characterization of different batches of pollen of Typha orientalis C.Presl were performed using UHPLC-Q-TOF/MS. Secondly, the direct inhibitory effects of pollen of T. orientalis on thrombin was assessed by using chromogenic substrate method together with HPLC. Thereafter, bioactive-chemical marker combination associated with anti-thrombin segregation was screened using supervised classifiers. Finally, quantitative assay and prediction-model of selected markers were established for guarantying the quality of pollen of T. orientalis.

RESULTS

A total of 22 compounds were annotated based on comparison with previous work from pollen of T. orientalis by UHPLC-Q-TOF/MS. Citric acid and linolenic acid inhibited the thrombin activity with IC₅₀ values, 0.52 ± 0.02 and 0.51 ± 0.02 mg/mL, respectively. A bioactive-chemical marker combination including citric acid, linolenic acid, typhaneoside, and isorhamnetin-3-O-neohesperidoside were discovered and selected as quality markers for evaluation of pollen of T. orientalis according to their capacity for inhibiting thrombin.

CONCLUSION

The thrombin-based discovery strategy of bioactive-chemical marker combination was a powerful tool for screening the quality markers for evaluation of pollen of T. orientalis.

Metabolomics of Myrcia bella Populations in Brazilian Savanna Reveals Strong Influence of Environmental Factors on Its Specialized Metabolism

Environmental conditions influence specialized plant metabolism. However, many studies aiming to understand these modulations have been conducted with model plants and/or under controlled conditions, thus not reflecting the complex interaction between plants and environment. To fully grasp these interactions, we investigated the specialized metabolism and genetic diversity of a native plant in its natural environment. We chose Myrcia bella due to its medicinal interest and occurrence in Brazilian savanna regions with diverse climate and soil conditions. An LC-HRMS-based metabolomics approach was applied to analyze 271 samples harvested across seven regions during the dry and rainy season. Genetic diversity was assessed in a subset of 40 samples using amplified fragment length polymorphism. Meteorological factors including rainfall, temperature, radiation, humidity, and soil nutrient and mineral composition were recorded in each region and correlated with chemical variation through multivariate analysis (MVDA). Marker compounds were selected using a statistically informed molecular network and annotated by dereplication against an in silico database of natural products. The integrated results evidenced different chemotypes, with variation in flavonoid and tannin content mainly linked to soil conditions. Different levels of genetic diversity and distance of populations were found to be correlated with the identified chemotypes. These observations and the proposed analytical workflow contribute to the global understanding of the impact of abiotic factors and genotype on the accumulation of given metabolites and, therefore, could be valuable to guide further medicinal exploration of native species.

Neuroprotective potential of Ayahuasca and untargeted metabolomics analyses: applicability to Parkinson's disease

ETHNOPHARMACOLOGY RELEVANCE

Ayahuasca is a tea produced through decoction of Amazonian plants. It has been used for centuries by indigenous people of South America. The beverage is considered to be an ethnomedicine, and it is traditionally used for the treatment of a wide range of diseases, including neurological illness. Besides, some scientific evidence suggests it may be applicable to Parkinson's disease (PD) treatment. Thus, Ayahuasca deserves in depth studies to clarify its potential role in this disease.

AIM OF THE STUDY

This study aimed to use an untargeted metabolomics approach to evaluate the neuroprotective potential of the Ayahuasca beverage, the extracts from its matrix plants (Banisteriopsis caapi and Psychotria viridis), its fractions and its main alkaloids on the viability of SH-SY5Y neuroblastoma cells in an in vitro PD model.

MATERIAL AND METHODS

The cytotoxicity of Ayahuasca, crude extracts, and fractions of B. caapi and P. viridis, as well as neuroprotection promoted by these samples in a 6-hydroxydopamine (6-OHDA)-induced neurodegeneration model, were evaluated by the MTT assay at two time-points: 48 h (T1) and 72 h (T2). The main alkaloids from Ayahuasca matrix plants, harmine (HRE) and N,N-dimethyltryptamine (DMT), were also isolated and evaluated. An untargeted metabolomics approach was developed to explore the chemical composition of samples with neuroprotective activity. Ultra-Performance Liquid Chromatography coupled to Electrospray Ionisation and Time-of-Flight (UPLC-ESI-TOF) metabolome data was treated and further analysed using multivariate statistical analyses (MSA): principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA). The metabolites were dereplicated using the Dictionary of Natural Products and an in house database. The main alkaloids were also quantified by UPLC-MS/MS.

RESULTS

The samples did not cause cytotoxicity in vitro and three of samples intensely increased cell viability at T1. The crude extracts, alkaloid fractions and HRE demonstrated remarkable neuroprotective effect at T2 while the hydroalcoholic fractions demonstrated this neuroprotective effect at T1 and T2. Several compounds from different classes, such as β-carbolines and monoterpene indole alkaloids (MIAs) were revealed correlated with this property by MSA. Additionally, a total of 2419 compounds were detected in both ionisation modes. HRE showed potent neuroprotective action at 72 h, but it was not among the metabolites positively correlated with the most efficacious neuroprotective profile at either time (T1 and T2). Furthermore, DMT was statistically important to differentiate the dataset (VIP value > 1), although it did not exhibit sufficient neuroprotective activity by in vitro assay, neither a positive correlation with T1 and T2 neuroprotective profile, which corroborated the MSA results.

CONCLUSION

The lower doses of the active samples stimulated neuronal cell proliferation and/or displayed the most efficacious neuroprotection profile, namely by preventing neuronal damage and improving cell viability against 6-OHDA-induced toxicity. Intriguingly, the hydroalcoholic fractions exhibited enhanced neuroprotective effects when compared to other samples and isolated alkaloids. This finding corroborates the significance of a holistic approach. The results demonstrate that Ayahuasca and its base plants have potential applicability for PD treatment and to prevent its progression differently from current drugs to treat PD.

Virgin olive oil metabolomics: A review

Metabolomics involvement in the study of foods is steadily growing. Such a rise is a consequence of the increasing demand in the food sector to address challenges regarding the issues of food safety, quality, and authenticity in a more comprehensive way. Virgin olive oil (VOO) is a key product of the Mediterranean diet, with a globalized consumer interest as it may be associated with various nutritional and health benefits. Despite the strict legislation to protect this high added-value agricultural commodity and offer guarantees to consumers and honest producers, there are still analytical issues needing to be further addressed. Thus, this review aims to present the efforts made using targeted and untargeted metabolomics approaches, namely nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry-based techniques (mainly LC/GC-MS) combined with multivariate statistical analysis. Case-studies focusing on geographical/varietal classification and detection of adulteration are discussed with regards to the identification of possible markers. The advantages and limitations of each of the aforementioned techniques applied to VOO analysis are also highlighted.

A novel binuclear Pd(ii) complex displaying synergic peptide cleavage behaviour

Mononuclear Pd(ii) complexes with two leaving groups are able to promote His-, Cys- and Met-orientated peptide hydrolysis, and exploring the peptide cleavage behavior of a novel Pd(ii) complex may provide "Omics" studies a promising artificial protease. In this study, a novel binuclear Pd(ii) complex [Pd₂(μ-O-L-H)(μ-Cl)](ClO₄)₂ (L = 2,6-bis(N-2'-aminoethylaminomethyl)-p-cresol) was constructed to promote peptide hydrolysis. Although each Pd(ii) center has only one leaving group (Cl) in this complex, electrophoresis and LC-MS-MS determination discloses that this complex enables myoglobin cleavage on the second upstream peptide bond from His and Met. A study on peptide cleavage also confirms the His- and Met-orientated peptide hydrolysis, yet no Cys-orientated hydrolysis was observed, although the cysteine-induced peptide/complex binding is distinct. Cysteine in the peptide even prevents the complex from promoting His-orientated hydrolysis, whereas the oxidized cysteine residue recovers the His-orientated hydrolysis. This peptide cleavage behavior is quite different from the simultaneous His-, Cys-, and Met-orientated hydrolysis promoted by the mononuclear Pd(ii) complexes. A theoretical study suggests that the two Pd(ii) centers of this complex might promote His- and Met-orientated hydrolysis in a synergic manner: one Pd(ii) center binds selectively on peptides or proteins and the other coordinates with the amide bond and water favoring nucleophilic attack on the peptide bond. The thiol group of cysteine is inclined to bridge the two Pd(ii) centers to form a "closed" sulphur-bridged structure, disfavoring the Cys-orientated hydrolysis. This study not only demonstrates the peptide cleavage behavior of this binuclear Pd(ii) complex, but also provides a polynuclear strategy to regulate the peptide cleavage behavior of Pd(ii) complexes.

Metabolic profiling of acromegaly using a GC-MS-based nontargeted metabolomic approach

PURPOSE

Acromegaly is a rare disease caused by chronic hypersecretion of growth hormone, which leads to multiple comorbidities and reduced life expectancy. The objective of this study was to characterize the serum metabolic profiles of acromegaly patients and identify metabolic biomarkers using metabolomics.

METHODS

Twenty-nine active acromegaly patients and age- and sex-matched normal controls were recruited. Serum samples were collected, and serum metabolites were analyzed using gas chromatography-mass spectrometry coupled with a series of multivariate statistical analyses.

RESULTS

The orthogonal projections to latent structures-discriminate analysis (OPLS-DA) model identified and validated significant metabolic differences between individuals with acromegaly and normal controls (R²Y = 0.908 and Q²Y = 0.601). Compared with normal controls, acromegaly patients had elevated levels of 5-aminovaleric acid, glyceric acid, L-dithiothreitol, dihydrocoumarin, N-acetyl-L-glutamic acid, gluconic acid, and monoolein (P < 0.05) and reduced serum levels of D-erythronolactone, taurine, carbamoyl-aspartic acid, and mucic acid (P < 0.01). Furthermore, glyceric acid and taurine possessed higher area under the receiver operating characteristic curve values (AUC values, 0.914 and 0.931, respectively), suggesting an excellent clinical ability to distinguish acromegaly patients from normal controls. Pathway analysis revealed that the pentose phosphate pathway and the taurine and hypotaurine metabolic pathway are significant pathways (P = 0.002 and 0.004, respectively).

CONCLUSIONS

Metabolic activity is significantly altered in the serum of individuals with active acromegaly. Glyceric acid and taurine may be considered potential biomarkers for distinguishing acromegaly patients from normal controls.

A complex matrix characterization approach, applied to cigarette smoke, that integrates multiple analytical methods and compound identification strategies for non-targeted liquid chromatography with high-resolution mass spectrometry

RATIONALE

For the characterization of the chemical composition of complex matrices such as tobacco smoke, containing more than 6000 constituents, several analytical approaches have to be combined to increase compound coverage across the chemical space. Furthermore, the identification of unknown molecules requiring the implementation of additional confirmatory tools in the absence of reference standards, such as tandem mass spectrometry spectra comparisons and in silico prediction of mass spectra, is a major bottleneck.

METHODS

We applied a combination of four chromatographic/ionization techniques (reversed-phase (RP) - heated electrospray ionization (HESI) in both positive (+) and negative (-) modes, RP - atmospheric pressure chemical ionization (APCI) in positive mode, and hydrophilic interaction liquid chromatography (HILIC) - HESI positive) using a Thermo Q Exactive™ liquid chromatography/high-resolution accurate mass spectrometry (LC/HRAM-MS) platform for the analysis of 3R4F-derived smoke. Compound identification was performed by using mass spectral libraries and in silico predicted fragments from multiple integrated databases.

RESULTS

A total of 331 compounds with semi-quantitative estimates ≥100 ng per cigarette were identified, which were distributed within the known chemical space of tobacco smoke. The integration of multiple LC/HRAM-MS-based chromatographic/ionization approaches combined with complementary compound identification strategies was key for maximizing the number of amenable compounds and for strengthening the level of identification confidence. A total of 50 novel compounds were identified as being present in tobacco smoke. In the absence of reference MS2 spectra, in silico MS2 spectra prediction gave a good indication for compound class and was used as an additional confirmatory tool for our integrated non-targeted screening (NTS) approach.

CONCLUSIONS

This study presents a powerful chemical characterization approach that has been successfully applied for the identification of novel compounds in cigarette smoke. We believe that this innovative approach has general applicability and a huge potential benefit for the analysis of any complex matrices.

Emerging Biomarkers for Prediction and Early Diagnosis of Necrotizing Enterocolitis in the Era of Metabolomics and Proteomics

Necrotizing Enterocolitis (NEC) is a catastrophic disease affecting predominantly premature infants and is characterized by high mortality and serious long-term consequences. Traditionally, diagnosis of NEC is based on clinical and radiological findings, which, however, are non-specific for NEC, thus confusing differential diagnosis of other conditions such as neonatal sepsis and spontaneous intestinal perforation. In addition, by the time clinical and radiological findings become apparent, NEC has already progressed to an advanced stage. During the last three decades, a lot of research has focused on the discovery of biomarkers, which could accurately predict and make an early diagnosis of NEC. Biomarkers used thus far in clinical practice include acute phase proteins, inflammation mediators, and molecules involved in the immune response. However, none has been proven accurate enough to predict and make an early diagnosis of NEC or discriminate clinical from surgical NEC or other non-NEC gastrointestinal diseases. Complexity of mechanisms involved in NEC pathogenesis, which remains largely poorly elucidated, could partly explain the unsatisfactory diagnostic performance of the existing NEC biomarkers. More recently applied technics can provide important insight into the pathophysiological mechanisms underlying NEC but can also aid the detection of potentially predictive, early diagnostic, and prognostic biomarkers. Progress in omics technology has allowed for the simultaneous measurement of a large number of proteins, metabolic products, lipids, and genes, using serum/plasma, urine, feces, tissues, and other biological specimens. This review is an update of current data on emerging NEC biomarkers detected using proteomics and metabolomics, further discussing limitations and future perspectives in prediction and early diagnosis of NEC.

Emerging Insights into the Metabolic Alterations in Aging Using Metabolomics

Metabolomics is the latest 'omics' technology and systems biology science that allows for comprehensive profiling of small-molecule metabolites in biological systems at a specific time and condition. Metabolites are cellular intermediate products of metabolic reactions, which reflect the ultimate response to genomic, transcriptomic, proteomic, or environmental changes in a biological system. Aging is a complex biological process that is characterized by a gradual and progressive decline in molecular, cellular, tissue, organ, and organismal functions, and it is influenced by a combination of genetic, environmental, diet, and lifestyle factors. The precise biological mechanisms of aging remain unknown. Metabolomics has emerged as a powerful tool to characterize the organism phenotypes, identify altered metabolites, pathways, novel biomarkers in aging and disease, and offers wide clinical applications. Here, I will provide a comprehensive overview of our current knowledge on metabolomics led studies in aging with particular emphasis on studies leading to biomarker discovery. Based on the data obtained from model organisms and humans, it is evident that metabolites associated with amino acids, lipids, carbohydrate, and redox metabolism may serve as biomarkers of aging and/or longevity. Current challenges and key questions that should be addressed in the future to advance our understanding of the biological mechanisms of aging are discussed.

Inborn Errors of Metabolism in the Era of Untargeted Metabolomics and Lipidomics

Inborn errors of metabolism (IEMs) are a group of inherited diseases with variable incidences. IEMs are caused by disrupting enzyme activities in specific metabolic pathways by genetic mutations, either directly or indirectly by cofactor deficiencies, causing altered levels of compounds associated with these pathways. While IEMs may present with multiple overlapping symptoms and metabolites, early and accurate diagnosis of IEMs is critical for the long-term health of affected subjects. The prevalence of IEMs differs between countries, likely because different IEM classifications and IEM screening methods are used. Currently, newborn screening programs exclusively use targeted metabolic assays that focus on limited panels of compounds for selected IEM diseases. Such targeted approaches face the problem of false negative and false positive diagnoses that could be overcome if metabolic screening adopted analyses of a broader range of analytes. Hence, we here review the prospects of using untargeted metabolomics for IEM screening. Untargeted metabolomics and lipidomics do not rely on predefined target lists and can detect as many metabolites as possible in a sample, allowing to screen for many metabolic pathways simultaneously. Examples are given for nontargeted analyses of IEMs, and prospects and limitations of different metabolomics methods are discussed. We conclude that dedicated studies are needed to compare accuracy and robustness of targeted and untargeted methods with respect to widening the scope of IEM diagnostics.

Study of Fecal and Urinary Metabolite Perturbations Induced by Chronic Ethanol Treatment in Mice by UHPLC-MS/MS Targeted Profiling

Alcoholic liver disease (ALD) as a consequence of ethanol chronic consumption could lead to hepatic cirrhosis that is linked to high morbidity and mortality. Disease diagnosis is still very challenging and usually clear findings are obtained in the later stage of ALD. The profound effect of ethanol on metabolism can be depicted using metabolomics; thus, the discovery of novel biomarkers could shed light on the initiation and the progression of the ALD, serving diagnostic purposes. In the present study, Hydrophilic Interaction Liquid Chromatography tandem Mass Spectrometry HILIC-MS/MS based metabolomics analyisis of urine and fecal samples of C57BL/6 mice of both sexes at two sampling time points was performed, monitoring the effect of eight-week ethanol consumption. The altered hepatic metabolism caused by ethanol consumption induces extensive biochemical perturbations and changes in gut microbiota population on a great scale. Fecal samples were proven to be a suitable specimen for studying ALD since it was more vulnerable to the metabolic changes in comparison to urine samples. The metabolome of male mice was affected on a greater scale than the female metabolome due to ethanol exposure. Precursor small molecules of essential pathways of energy production responded to ethanol exposure. A meaningful correlation between the two studied specimens demonstrated the impact of ethanol in endogenous and symbiome metabolism.

Sulfadiazine Sodium Ameliorates the Metabolomic Perturbation in Mice Infected with Toxoplasma gondii

In this study, we analyzed the global metabolomic changes associated with Toxoplasma gondii infection in mice in the presence or absence of sulfadiazine sodium (SDZ) treatment. BALB/c mice were infected with T. gondii GT1 strain and treated orally with SDZ (250 μg/ml in water) for 12 consecutive days. Mice showed typical manifestations of illness at 20 days postinfection (dpi); by 30 dpi, 20% had survived and developed latent infection. We used ultraperformance liquid chromatography-mass spectrometry to profile the serum metabolomes in control (untreated and uninfected) mice, acutely infected mice, and SDZ-treated and infected mice. Infection induced significant perturbations in the metabolism of α-linolenic acid, purine, pyrimidine, arginine, tryptophan, valine, glycerophospholipids, and fatty acyls. However, treatment with SDZ seemed to alleviate the serum metabolic alterations caused by infection. The restoration of the serum metabolite levels in the treated mice was associated with better clinical outcomes. These data indicate that untargeted metabolomics can reveal biochemical pathways associated with restoration of the metabolic status of T. gondii-infected mice following SDZ treatment and could be used to monitor responses to SDZ treatment. This study provides a new systems approach to elucidate the metabolic and therapeutic effects of SDZ in the context of murine toxoplasmosis.

Untargeted LC/MS-based metabolic phenotyping (metabonomics/metabolomics): The state of the art

Liquid chromatography (LC) hyphenated to mass spectrometry is currently the most widely used means of determining metabolic phenotypes via both untargeted and targeted analysis. At present a range of analytical separations, including reversed-phase, hydrophilic interaction and ion-pair LC are employed to maximise metabolome coverage with ultra (high) performance liquid chromatography (UHPLC) increasingly displacing conventional high performance liquid chromatography because of the need for short analysis times and high peak capacity in such applications. However, it is widely recognized that these methodologies do not entirely solve the problems facing researchers trying to perform comprehensive metabolic phenotyping and in addition to these "routine" approaches there are continuing investigations of alternative separation methods including 2-dimensional/multi column approaches. These involve either new stationary phases or multidimensional combinations of the more conventional materials currently used, as well as application of miniaturization or "new" approaches such as supercritical HP and UHP- chromatographic separations. There is also a considerable amount of interest in the combination of chromatographic and ion mobility separations, with the latter providing both an increase in resolution and the potential to provide additional structural information via the determination of molecular collision cross section data. However, key problems remain to be solved including ensuring quality, comparability across different laboratories and the ever present difficulty of identifying unknowns.