Multiplatform Analytical Methodology for Metabolic Fingerprinting of Lung Tissue

Exploring sample treatment strategies for untargeted metabolomics: A comparative study of solid phase microextraction (SPME) and homogenization with solid-liquid extraction (SLE) in renal tissue

BACKGROUND

The selection of the sample treatment strategy is a crucial step in the metabolomics workflow. Solid phase microextraction (SPME) is a sample processing methodology with great potential for use in untargeted metabolomics of tissue samples. However, its utilization is not as widespread as other standard protocols involving steps of tissue collection, metabolism quenching, homogenization, and extraction of metabolites by solvents. Since SPME allows us to perform all these steps in one action in tissue samples, in addition to other advantages, it is necessary to know whether this methodology produces similar or comparable metabolome and lipidome coverage and performance to classical methods.

RESULTS

SPME and homogenization with solid-liquid extraction (Homo-SLE) sample treatment methods were applied to healthy murine kidney tissue, followed by comprehensive metabolomics and lipidomics analyses. In addition, it has been tested whether freezing and storage of the tissue causes alterations in the renal metabolome and lipidome, so the analyses were performed on fresh and frozen tissue samples Lipidomics analysis revealed the exclusive presence of different structural membrane and intracellular lipids in the Homo-SLE group. Conversely, all annotated metabolites were detected in both groups. Notably, the freezing of the sample mainly causes a decrease in the levels of most lipid species and an increase in metabolites such as amino acids, purines, and pyrimidines. These alterations are principally detected in a statistically significant way by SPME methodology. Finally, the samples of both methodologies show a positive correlation in all the analyses.

SIGNIFICANCE

These results demonstrate that in SPME processing, as long as the fundamentals of non-exhaustive extraction in a pre-equilibrium kinetic regime, extraction in a tissue localized area, the chemistry of the fiber coating and non-homogenization of the tissue are taken into account, is an excellent method to use in kidney tissue metabolomics; since this methodology presents an easy-to-use, efficient, and less invasive approach that simplifies the different sample processing steps.

A diverse proteome is present and enzymatically active in metabolite extracts

Metabolite extraction is the critical first-step in metabolomics experiments, where it is generally regarded to inactivate and remove proteins. Here, arising from efforts to improve extraction conditions for polar metabolomics, we discover a proteomic landscape of over 1000 proteins within metabolite extracts. This is a ubiquitous feature across several common extraction and sample types. By combining post-resuspension stable isotope addition and enzyme inhibitors, we demonstrate in-extract metabolite interconversions due to residual transaminase activity. We extend these findings with untargeted metabolomics where we observe extensive protein-mediated metabolite changes, including in-extract formation of glutamate dipeptide and depletion of total glutathione. Finally, we present a simple extraction workflow that integrates 3 kDa filtration for protein removal as a superior method for polar metabolomics. In this work, we uncover a previously unrecognized, protein-mediated source of observer effects in metabolomics experiments with broad-reaching implications across all research fields using metabolomics and molecular metabolism.

LiLA: lipid lung-based ATLAS built through a comprehensive workflow designed for an accurate lipid annotation

Accurate lipid annotation is crucial for understanding the role of lipids in health and disease and identifying therapeutic targets. However, annotating the wide variety of lipid species in biological samples remains challenging in untargeted lipidomic studies. In this work, we present a lipid annotation workflow based on LC-MS and MS/MS strategies, the combination of four bioinformatic tools, and a decision tree to support the accurate annotation and semi-quantification of the lipid species present in lung tissue from control mice. The proposed workflow allowed us to generate a lipid lung-based ATLAS (LiLA), which was then employed to unveil the lipidomic signatures of the Mycobacterium tuberculosis infection at two different time points for a deeper understanding of the disease progression. This workflow, combined with manual inspection strategies of MS/MS data, can enhance the annotation process for lipidomic studies and guide the generation of sample-specific lipidome maps. LiLA serves as a freely available data resource that can be employed in future studies to address lipidomic alterations in mice lung tissue.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Multiplatform untargeted metabolomics

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize a few hundred metabolites at best. The uncertainty in metabolite identification commonly encountered in untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple analytical techniques) approach can improve upon the number of metabolites reliably detected and correctly assigned. This can be further improved by applying synergistic sample preparation along with the use of combinatorial or sequential non-destructive and destructive techniques. Similarly, peak detection and metabolite identification strategies that employ multiple probabilistic approaches have led to better annotation decisions. Applying these techniques also addresses the issues of reproducibility found in single platform methods. Nevertheless, the analysis of large data sets from disparate analytical techniques presents unique challenges. While the general data processing workflow is similar across multiple platforms, many software packages are only fully capable of processing data types from a single analytical instrument. Traditional statistical methods such as principal component analysis were not designed to handle multiple, distinct data sets. Instead, multivariate analysis requires multiblock or other model types for understanding the contribution from multiple instruments. This review summarizes the advantages, limitations, and recent achievements of a multiplatform approach to untargeted metabolomics.

Impact of renal tubular Cpt1a overexpression on the kidney metabolome in the folic acid-induced fibrosis mouse model

Background: Chronic kidney disease (CKD) is characterized by the progressive and irreversible deterioration of kidney function and structure with the appearance of renal fibrosis. A significant decrease in mitochondrial metabolism, specifically a reduction in fatty acid oxidation (FAO) in tubular cells, is observed in tubulointerstitial fibrosis, whereas FAO enhancement provides protection. Untargeted metabolomics offers the potential to provide a comprehensive analysis of the renal metabolome in the context of kidney injury. Methodology: Renal tissue from a carnitine palmitoyl transferase 1a (Cpt1a) overexpressing mouse model, which displays enhanced FAO in the renal tubule, subjected to folic acid nephropathy (FAN) was studied through a multiplatform untargeted metabolomics approach based on LC-MS, CE-MS and GC-MS analysis to achieve the highest coverage of the metabolome and lipidome affected by fibrosis. The expression of genes related to the biochemical routes showing significant changes was also evaluated. Results: By combining different tools for signal processing, statistical analysis and feature annotation, we were able to identify variations in 194 metabolites and lipids involved in many metabolic routes: TCA cycle, polyamines, one-carbon metabolism, amino acid metabolism, purine metabolism, FAO, glycerolipids and glycerophospholipids synthesis and degradation, glycosphingolipids interconversion, and sterol metabolism. We found several metabolites strongly altered by FAN, with no reversion induced by Cpt1a overexpression (v.g. citric acid), whereas other metabolites were influenced by CPT1A-induced FAO (v.g. glycine-betaine). Conclusion: It was implemented a successful multiplatform metabolomics approach for renal tissue analysis. Profound metabolic changes accompany CKD-associated fibrosis, some associated with tubular FAO failure. These results highlight the importance of addressing the crosstalk between metabolism and fibrosis when undertaking studies attempting to elucidate the mechanism of CKD progression.

Relationship between 4-Hydroxynonenal (4-HNE) as Systemic Biomarker of Lipid Peroxidation and Metabolomic Profiling of Patients with Prostate Cancer

An oxidative degradation product of the polyunsaturated fatty acids, 4-hydroxynonenal (4-HNE), is of particular interest in cancer research due to its concentration-dependent pleiotropic activities affecting cellular antioxidants, metabolism, and growth control. Although an increase in oxidative stress and lipid peroxidation was already associated with prostate cancer progression a few decades ago, the knowledge of the involvement of 4-HNE in prostate cancer tumorigenesis is limited. This study investigated the appearance of 4-HNE-protein adducts in prostate cancer tissue by immunohistochemistry using a genuine 4-HNE monoclonal antibody. Plasma samples of the same patients and samples of the healthy controls were also analyzed for the presence of 4-HNE-protein adducts, followed by metabolic profiling using LC-ESI-QTOF-MS and GC-EI-Q-MS. Finally, the analysis of the metabolic pathways affected by 4-HNE was performed. The obtained results revealed the absence of 4-HNE-protein adducts in prostate carcinoma tissue but increased 4-HNE-protein levels in the plasma of these patients. Metabolomics revealed a positive association of different long-chain and medium-chain fatty acids with the presence of prostate cancer. Furthermore, while linoleic acid positively correlated with the levels of 4-HNE-protein adducts in the blood of healthy men, no correlation was obtained for cancer patients indicating altered lipid metabolism in this case. The metabolic pathway of unsaturated fatty acids biosynthesis emerged as significantly affected by 4-HNE. Overall, this is the first study linking 4-HNE adduction to plasma proteins with specific alterations in the plasma metabolome of prostate cancer patients. This study revealed that increased 4-HNE plasma protein adducts could modulate the unsaturated fatty acids biosynthesis pathway. It is yet to be determined if this is a direct result of 4-HNE or whether they are produced by the same underlying mechanisms. Further mechanistic studies are needed to grasp the biological significance of the observed changes in prostate cancer tumorigenesis.

A Metabolic Signature of Hereditary Transthyretin Amyloidosis: A Pilot Study

Hereditary transthyretin amyloidosis is the most common form of hereditary amyloidosis, with an autosomal dominant inheritance and a variable penetrance. ATTRv amyloidosis can present as a progressive, axonal sensory autonomic and motor neuropathy or as an infiltrative cardiomyopathy. The definition of biomarkers for the early diagnosis of ATTRv is particularly important in the current era of emerging treatments. In this sense, metabolomics could be an instrument able to provide metabolic profiles with their related metabolic pathways, and we would propose them as possible fluid biomarkers. The aim of this study is to identify altered metabolites (free fatty acids and amino acids) in subjects with a confirmed pathogenic TTR variant. Out of the studied total free fatty acids and amino acids, the serum values of palmitic acid are significantly lower in the ATTRv patients compared to the recruited healthy subjects. The metabolic remodeling identified in this neurogenetic disorder could be the manifestation of pathophysiological processes of the disease, such as mitochondrial dysfunction and neuroinflammation, and contribute to explaining some of its clinical manifestations.

Mitochondrial citrate accumulation drives alveolar epithelial cell necroptosis in lipopolysaccharide-induced acute lung injury

Necroptosis is the major cause of death in alveolar epithelial cells (AECs) during acute lung injury (ALI). Here, we report a previously unrecognized mechanism for necroptosis. We found an accumulation of mitochondrial citrate (citrate^mt) in lipopolysaccharide (LPS)-treated AECs because of the downregulation of Idh3α and citrate carrier (CIC, also known as Slc25a1). shRNA- or inhibitor-mediated inhibition of Idh3α and Slc25a1 induced citrate^mt accumulation and necroptosis in vitro. Mice with AEC-specific Idh3α and Slc25a1 deficiency exhibited exacerbated lung injury and AEC necroptosis. Interestingly, the overexpression of Idh3α and Slc25a1 decreased citrate^mt levels and rescued AECs from necroptosis. Mechanistically, citrate^mt accumulation induced mitochondrial fission and excessive mitophagy in AECs. Furthermore, citrate^mt directly interacted with FUN14 domain-containing protein 1 (FUNDC1) and promoted the interaction of FUNDC1 with dynamin-related protein 1 (DRP1), leading to excessive mitophagy-mediated necroptosis and thereby initiating and promoting ALI. Importantly, necroptosis induced by citrate^mt accumulation was inhibited in FUNDC1-knockout AECs. We show that citrate^mt accumulation is a novel target for protection against ALI involving necroptosis.

Low and high resolution gas chromatography-mass spectrometry for untargeted metabolomics: A tutorial

GC-MS for untargeted metabolomics is a well-established technique. Small molecules and molecules made volatile by derivatization can be measured and those compounds are key players in main biological pathways. This tutorial provides ready-to-use protocols for GC-MS-based metabolomics, using either the well-known low-resolution approach (GC-Q-MS) with nominal mass or the more recent high-resolution approach (GC-QTOF-MS) with accurate mass, discussing their corresponding strengths and limitations. Analytical procedures are covered for different types of biofluids (plasma/serum, bronchoalveolar lavage, urine, amniotic fluid) tissue samples (brain/hippocampus, optic nerve, lung, kidney, liver, pancreas) and samples obtained from cell cultures (adipocytes, macrophages, Leishmania promastigotes, mitochondria, culture media). Together with the sample preparation and data acquisition, data processing strategies are described specially focused on Agilent equipments, including deconvolution software and database annotation using spectral libraries. Manual curation strategies and quality control are also deemed. Finally, considerations to obtain a semiquantitative value for the metabolites are also described. As a case study, an illustrative example from one of our experiments at CEMBIO Research Centre, is described and findings discussed.

A Set of Reliable Samples for the Study of Biomarkers for the Early Diagnosis of Parkinson's Disease

Background

Parkinson's disease (PD) is a progressive neurodegenerative disorder, diagnosed according to the clinical criteria that occur in already advanced stages of PD. The definition of biomarkers for the early diagnosis of PD represents a challenge that might improve treatment and avoid complications in this disease. Therefore, we propose a set of reliable samples for the identification of altered metabolites to find potential prognostic biomarkers for early PD.

Methods

This case–control study included plasma samples of 12 patients with PD and 21 control subjects, from the Spanish European Prospective Investigation into Cancer and Nutrition (EPIC)-Navarra cohort, part of the EPIC-Spain study. All the case samples were provided by healthy volunteers who were followed-up for 15.9 (±4.1) years and developed PD disease later on, after the sample collection. Liquid chromatography coupled to tandem mass spectrometry was used for the analysis of samples.

Results

Out of 40 that were selected and studied due to their involvement in established cases of PD, seven significantly different metabolites between PD cases and healthy control subjects were obtained in this study (benzoic acid, palmitic acid, oleic acid, stearic acid, myo-inositol, sorbitol, and quinolinic acid). These metabolites are related to mitochondrial dysfunction, the oxidative stress, and the mechanisms of energy production.

Conclusion

We propose the samples from the EPIC study as reliable and invaluable samples for the search of early biomarkers of PD. Likewise, this study might also be a starting point in the establishment of a well-founded panel of metabolites that can be used for the early detection of this disease.

Metabolomic profiling of peripheral plasma by GC-MS and correlation with size of uterine leiomyomas

Background

Uterine leiomyomas are benign monoclonal tumors originating from the myometrium. Little information exists concerning metabolomics and the presence of leiomyomas.

Objective

The present study evaluated circulating metabolites in the plasma and their correlation with the presence and size of leiomyomas.

Study Design

Cross-sectional observational study, including women divided into 3 groups: 37 with leiomyomas and uterus >500 cm³, 17 with leiomyomas and uterus ≤150 cm³, and 21 leiomyoma-free. Patients underwent peripheral blood collection using untargeted metabolic assessment by gas chromatography coupled to mass spectrometer.

Results

There was no statistical difference between patients’ anthropometric and demographic features and laboratory tests. Statistical differences in uterus volume (P < 0.0001) were found. Forty-six metabolites were identified (35% amino acids and derivatives, 22% fatty acids, and 18% carbohydrates). Statistically significant metabolic distinction (P < 0.05, false discovery rate< 0.05) was observed for 14 metabolites. Most amino acids (L-isoleucine, L-valine, and pyroglutamic acid) were significantly reduced in plasma levels of patients with large leiomyomas. The only exception was L-glutamine, with a significant increase. Fatty acids (arachidonic acid, alfa-tocopherol, palmitic acid, and stearic acid) were similarly reduced in large leiomyomas patients, except for alpha-linolenic acid, which increased. For carbohydrates (myo-inositol, D-threitol, and D-ribose), there was a decrease in the plasma of patients with leiomyomas.

Conclusion

There are different plasma metabolites levels of amino acids, fatty acids, and carbohydrates among patients with leiomyomas, most of them reduced, but some significantly increased in large leiomyomas, compared to leiomyoma-free patients.

Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC)

INTRODUCTION

The metabolomics quality assurance and quality control consortium (mQACC) is enabling the identification, development, prioritization, and promotion of suitable reference materials (RMs) to be used in quality assurance (QA) and quality control (QC) for untargeted metabolomics research.

OBJECTIVES

This review aims to highlight current RMs, and methodologies used within untargeted metabolomics and lipidomics communities to ensure standardization of results obtained from data analysis, interpretation and cross-study, and cross-laboratory comparisons. The essence of the aims is also applicable to other 'omics areas that generate high dimensional data.

RESULTS

The potential for game-changing biochemical discoveries through mass spectrometry-based (MS) untargeted metabolomics and lipidomics are predicated on the evolution of more confident qualitative (and eventually quantitative) results from research laboratories. RMs are thus critical QC tools to be able to assure standardization, comparability, repeatability and reproducibility for untargeted data analysis, interpretation, to compare data within and across studies and across multiple laboratories. Standard operating procedures (SOPs) that promote, describe and exemplify the use of RMs will also improve QC for the metabolomics and lipidomics communities.

CONCLUSIONS

The application of RMs described in this review may significantly improve data quality to support metabolomics and lipidomics research. The continued development and deployment of new RMs, together with interlaboratory studies and educational outreach and training, will further promote sound QA practices in the community.

Transforming growth factor β3 deficiency promotes defective lipid metabolism and fibrosis in murine kidney

Glomerulosclerosis and tubulointerstitial fibrosis are pathological features of chronic kidney disease. Transforming growth factor β (TGFβ) is a key player in the development of fibrosis. However, of the three known TGFβ isoforms, only TGFβ1 has an established role in fibrosis, and the pathophysiological relevance of TGFβ2 and TGFβ3 is unknown. Because Tgfb3 deficiency in mice results in early postnatal lethality, we analyzed the kidney phenotype of heterozygous Tgfb3-knockout mice (Tgfb3^+/−) and compared it with that of matched wild-type mice. Four-month-old Tgfb3^+/− mice exhibited incipient renal fibrosis with epithelial–mesenchymal transition, in addition to glomerular basement membrane thickening and podocyte foot process effacement associated with albuminuria. Also evident was insulin resistance and oxidative stress at the renal level, together with aberrant renal lipid metabolism and mitochondrial function. Omics analysis revealed toxic species, such as diacylglycerides and ceramides, and dysregulated mitochondrial metabolism in Tgfb3^+/− mice. Kidneys of Tgfb3^+/− mice showed morphological alterations of mitochondria and overactivation of non-canonical MAPK ERK1/2 and JNK cascades. Our study indicates that renal TGFβ3 might have antifibrotic and renoprotective properties, opposing or counteracting the activity of TGFβ1.

This article has an associated First Person interview with the first author of the paper.

Summary: Our study describes the renal abnormalities of heterozygous Tgfb3-targeted mice and suggests that TGFβ3 is renoprotective and may counteract the activity of TGFβ1.

A Cross-Platform Metabolomics Comparison Identifies Serum Metabolite Signatures of Liver Fibrosis Progression in Chronic Hepatitis C Patients

Metabolomics offers new insights into disease mechanisms that is enhanced when adopting orthogonal instrumental platforms to expand metabolome coverage, while also reducing false discoveries by independent replication. Herein, we report the first inter-method comparison when using multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS) and nuclear magnetic resonance (NMR) spectroscopy for characterizing the serum metabolome of patients with liver fibrosis in chronic hepatitis C virus (HCV) infection (n = 20) and non-HCV controls (n = 14). In this study, 60 and 30 serum metabolites were detected frequently (>75%) with good technical precision (median CV < 10%) from serum filtrate samples (n = 34) when using standardized protocols for MSI-CE-MS and NMR, respectively. Also, 20 serum metabolite concentrations were consistently measured by both methods over a 500-fold concentration range with an overall mean bias of 9.5% (n = 660). Multivariate and univariate statistical analyses independently confirmed that serum choline and histidine were consistently elevated (p < 0.05) in HCV patients with late-stage (F2-F4) as compared to early-stage (F0-F1) liver fibrosis. Overall, the ratio of serum choline to uric acid provided optimal differentiation of liver disease severity (AUC = 0.848, p = 0.00766) using a receiver operating characteristic curve, which was positively correlated with liver stiffness measurements by ultrasound imaging (r = 0.606, p = 0.0047). Moreover, serum 5-oxo-proline concentrations were higher in HCV patients as compared to non-HCV controls (F = 4.29, p = 0.0240) after adjustment for covariates (age, sex, BMI), indicative of elevated oxidative stress from glutathione depletion with the onset and progression of liver fibrosis. Both instrumental techniques enable rapid yet reliable quantification of serum metabolites in large-scale metabolomic studies with good overlap for biomarker replication. Advantages of MSI-CE-MS include greater metabolome coverage, lower operating costs, and smaller sample volume requirements, whereas NMR offers a robust platform supported by automated spectral and data processing software.

Metabolomics analysis provides new insights into the medicinal value of flavonoids in tobacco leaves

Tobacco is a traditional Chinese medicine containing a variety of biologically active substances. In addition to being used to make cigarettes, tobacco is also a vastly underdeveloped medicinal resource. In order to identify and clarify the biological activities and medicinal value of tobacco leaves, the metabolomes of tobacco leaves were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) based on multiple reaction monitoring (MRM). In total, 1169 metabolites were identified and quantified. The results showed that the metabolic profiles of the tobacco cultivars K326 and Yun87 are similar to each other but different from that of Hongda. Moreover, the curing process affects the metabolic profiles of tobacco leaves. Flavonoids are the largest class of metabolites in tobacco leaves. Flavonoids have multiple biological functions; for example, they can promote or inhibit inflammation. We found that quercetin provides anti-inflammatory activity by inhibiting the il-1β mRNA expression, while glycitin and neohesperidin can promote il-1β and il-6 production. Our results provide in-depth insights into the medical uses and biological mechanisms of tobacco leaves.

The Importance of Metabolism for Immune Homeostasis in Allergic Diseases

There is increasing evidence that the metabolic status of T cells and macrophages is associated with severe phenotypes of chronic inflammation, including allergic inflammation. Metabolic changes in immune cells have a crucial role in their inflammatory or regulatory responses. This notion is reinforced by metabolic diseases influencing global energy metabolism, such as diabetes or obesity, which are known risk factors of severity in inflammatory conditions, due to the metabolic-associated inflammation present in these patients. Since several metabolic pathways are closely tied to T cell and macrophage differentiation, a better understanding of metabolic alterations in immune disorders could help to restore and modulate immune cell functions. This link between energy metabolism and inflammation can be studied employing animal, human or cellular models. Analytical approaches rank from classic immunological studies to integrated analysis of metabolomics, transcriptomics, and proteomics. This review summarizes the main metabolic pathways of the cells involved in the allergic reaction with a focus on T cells and macrophages and describes different models and platforms of analysis used to study the immune system and its relationship with metabolism.

Capillary Electrophoresis-Mass Spectrometry for Metabolomics: Possibilities and Perspectives

Capillary electrophoresis-mass spectrometry (CE-MS) is a very useful analytical technique for the selective and highly efficient profiling of polar and charged metabolites in a wide range of biological samples. Compared to other analytical techniques, the use of CE-MS in metabolomics is relatively low as the approach is still regarded as technically challenging and not reproducible. In this chapter, the possibilities of CE-MS for metabolomics are highlighted with special emphasis on the use of recently developed interfacing designs. The utility of CE-MS for targeted and untargeted metabolomics studies is demonstrated by discussing representative and recent examples in the biomedical and clinical fields. The potential of CE-MS for large-scale and quantitative metabolomics studies is also addressed. Finally, some general conclusions and perspectives are given on this strong analytical separation technique for probing the polar metabolome.

Metabolomics in posttraumatic stress disorder: Untargeted metabolomic analysis of plasma samples from Croatian war veterans

Posttraumatic stress disorder (PTSD) is a severe, multifactorial and debilitating neuropsychiatric disorder, which can develop in a subset of individuals as a result of the exposure to severe stress or trauma. Such traumatic experiences have a major impact on molecular, biochemical and cellular systems, causing psychological and somatic alterations that affect the whole organism. Although the etiology of PTSD is still unclear, it seems to involve complex interaction between various biological genetic and environmental factors. Metabolomics, as one of the rapidly developing "omics" techniques, might be a useful tool for determining altered metabolic pathways and stress-related metabolites as new potential biomarkers of PTSD. The aim of our study was to identify metabolites whose altered levels allow us to differentiate between patients with PTSD and healthy control individuals. The study included two cohorts. The first, exploratory, group included 50 Croatian veterans with PTSD and 50 healthy control subjects, whereas a validation group consisted of 52 veterans with PTSD and 52 control subjects. The metabolomic analysis of plasma samples was conducted using liquid chromatography coupled with mass spectrometry (LC-MS), as well as gas chromatography coupled with mass spectrometry (GC-MS). The LC-MS analysis determined significantly different levels of two glycerophospholipids, PE(18:1/0:0) and PC(18:1/0:0), between control subjects and PTSD patients in both cohorts. The altered metabolites might play a role in multiple cellular processes, including inflammation, mitochondrial dysfunction, membrane breakdown, oxidative stress and neurotoxicity, which could be associated with PTSD pathogenesis.

Insulin Resistance in Obese Children: What Can Metabolomics and Adipokine Modelling Contribute?

The evolution of obesity and its resulting comorbidities differs depending upon the age of the subject. The dramatic rise in childhood obesity has resulted in specific needs in defining obesity-associated entities with this disease. Indeed, even the definition of obesity differs for pediatric patients from that employed in adults. Regardless of age, one of the earliest metabolic complications observed in obesity involves perturbations in glucose metabolism that can eventually lead to type 2 diabetes. In children, the incidence of type 2 diabetes is infrequent compared to that observed in adults, even with the same degree of obesity. In contrast, insulin resistance is reported to be frequently observed in children and adolescents with obesity. As this condition can be prerequisite to further metabolic complications, identification of biological markers as predictive risk factors would be of tremendous clinical utility. Analysis of obesity-induced modifications of the adipokine profile has been one classic approach in the identification of biomarkers. Recent studies emphasize the utility of metabolomics in the analysis of metabolic characteristics in children with obesity with or without insulin resistance. These studies have been performed with targeted or untargeted approaches, employing different methodologies. This review summarizes some of the advances in this field while emphasizing the importance of the different techniques employed.

Comprehensive Examination of the Mouse Lung Metabolome Following Mycobacterium tuberculosis Infection Using a Multiplatform Mass Spectrometry Approach

The mechanisms whereby Mycobacterium tuberculosis (Mtb) rewires the host metabolism in vivo are surprisingly unexplored. Here, we used three high-resolution mass spectrometry platforms to track altered lung metabolic changes associated with Mtb infection of mice. The multiplatform data sets were merged using consensus orthogonal partial least squares-discriminant analysis (cOPLS-DA), an algorithm that allows for the joint interpretation of the results from a single multivariate analysis. We show that Mtb infection triggers a temporal and progressive catabolic state to satisfy the continuously changing energy demand to control infection. This causes dysregulation of metabolic and oxido-reductive pathways culminating in Mtb-associated wasting. Notably, high abundances of trimethylamine-N-oxide (TMAO), produced by the host from the bacterial metabolite trimethylamine upon infection, suggest that Mtb could exploit TMAO as an electron acceptor under anaerobic conditions. Overall, these new pathway alterations advance our understanding of the link between Mtb pathogenesis and metabolic dysregulation and could serve as a foundation for new therapeutic intervention strategies. Mass spectrometry data has been deposited in the Metabolomics Workbench repository (data-set identifier: ST001328).

Metabolic impact of partial hepatectomy in the non-alcoholic steatohepatitis animal model of methionine-choline deficient diet

In the liver, obesity is often manifested by the clinical disorder of the Non-Alcoholic Fatty Liver Disease (NAFLD). A proportion of NAFLD patients develop hepatic inflammation, known as Non-Alcoholic Steatohepatitis (NASH), which can end up in cirrhosis, or Hepatocellular Carcinoma (HCC). In this scenario, partial hepatectomy (PH) is an alternative to promote liver regeneration. However, as liver regeneration is impaired in NASH patients, more knowledge about its metabolic condition is needed to improve the regenerative response of the liver in this pathological condition. Although extensively employed, the panoply of molecular alterations involved in the regenerative response of the liver after partial hepatectomy PH is far from being fully characterized. Metabolic fingerprinting (metabolomics) is a powerful tool to help in the elucidation of complex metabolic networks, by means of a blind, naïve approach to study which metabolic nodes (metabolites) show the biggest variations between conditions. The objective of the present study was to gain deeper knowledge about the metabolic processes involved in the NASH animal model, and particularly in the effect of PH by using metabolomics. For achieving such information, twelve 8-week-old male C57BL/6 J mice, fed commercial chow (control diet) or methionine and choline-Deficient diet (MCD) for three weeks were subjected to PH and sacrificed 2 weeks later. Livers were removed and submitted to metabolic profiling analysis through RP-LC/MS (qTOF), GC/MS (qTOF) and CE/MS(TOF). More than 3000 different features were detected and repeated measurements one-way ANOVA analysis was performed to unveil significant features. MCD diet induced changes (p < 0.05) in 46% of the detected features, whereas PH provoked significant changes in 85% of them. Most of the changes were detected through LC/MS and were associated to lipid metabolism. However, changes of metabolites virtually related to other metabolic routes (amino acids, carbohydrates, nucleotides) were found altered and detected by CE/MS and GC/MS. The changes associated to PH show a similar trend regardless of the diet, but in the context of the diet deficient in methionine and choline we have found results that point to a different ratio glycolysis/tricarboxylic acid cycle. Moreover, in the NASH model, the regeneration of the liver structures occurs at the expense of an increased phosphatidylethanolamines/phosphatidylcholines ratio.

CE-MS for anionic metabolic profiling: An overview of methodological developments

The efficient profiling of highly polar and charged metabolites in biological samples remains a huge analytical challenge in metabolomics. Over the last decade, new analytical techniques have been developed for the selective and sensitive analysis of polar ionogenic compounds in various matrices. Still, the analysis of such compounds, notably for acidic ionogenic metabolites, remains a challenging endeavor, even more when the available sample size becomes an issue for the total analytical workflow. In this paper, we give an overview of the possibilities of capillary electrophoresis-mass spectrometry (CE-MS) for anionic metabolic profiling by focusing on main methodological developments. Attention is paid to the development of improved separation conditions and new interfacing designs in CE-MS for anionic metabolic profiling. A complete overview of all CE-MS-based methods developed for this purpose is provided in table format (Table 1) which includes information on sample type, separation conditions, mass analyzer and limits of detection (LODs). Selected applications are discussed to show the utility of CE-MS for anionic metabolic profiling, especially for small-volume biological samples. On the basis of the examination of the reported literature in this specific field, we conclude that there is still room for the design of a highly sensitive and reliable CE-MS method for anionic metabolic profiling. A rigorous validation and the availability of standard operating procedures would be highly favorable in order to make CE-MS an alternative, viable analytical technique for metabolomics.

Metabolomic Heterogeneity of Urogenital Tract Cancers Analyzed by Complementary Chromatographic Techniques Coupled with Mass Spectrometry

BACKGROUND

In regard to urogenital tract cancer studies, an estimated 340,650 new cases and 58,360 deaths from genital system cancer and about 141,140 new cases and 29330 deaths from urinary system were projected to occur in the United States in 2012. The main drawbacks of currently available diagnostic tests constitute the low specificity, costliness and quite high invasiveness.

OBJECTIVE

The main goal of this pilot study was to determine and compare urine metabolic fingerprints in urogenital tract cancer patients and healthy controls.

METHOD

A comparative analysis of the metabolic profile of urine from 30 patients with cancer of the genitourinary system (bladder (n=10), kidney (n=10) and prostate (n=10)) and 30 healthy volunteers as a control group was provided by LC-TOF/MS and GCQqQ/ MS. The data analysis was performed by the use of U-Mann Whitney test or Student's t-test, principal component analysis (PCA) and orthogonal partial least-squares discriminant analysis (OPLS-DA).

RESULTS

As a result, 33, 43, and 22 compounds were identified as statistically significant in bladder, prostate and kidney cancer, respectively, compared to healthy groups.

CONCLUSION

Diverse compounds such as purine, sugars, amino acids, nucleosides, organic acids which play a role in purine metabolism, in tricarboxylic acid cycle, in amino acid metabolism or in gut microbiota metabolism were identified. Only two metabolites namely glucocaffeic acid and lactic acid were found to be in common in studied three types of cancer.

Metabolomics reveals citric acid secretion in mechanically-stimulated osteocytes is inhibited by high glucose

Osteocytes are the main cells of bone tissue and play a crucial role in bone formation and resorption. Recent studies have indicated that Diabetes Mellitus (DM) affects bone mass and potentially causes higher bone fracture risk. Previous work on osteocyte cell cultures has demonstrated that mechanotransduction is impaired after culture under diabetic pre-conditioning with high glucose (HG), specifically osteoclast recruitment and differentiation. The aim of this study was to analyze the extracellular metabolic changes of osteocytes regarding two conditions: pre-conditioning to either basal levels of glucose (B), mannitol (M) or HG cell media, and mechanical stimulation by fluid flow (FF) in contrast to static condition (SC). Secretomes were analyzed using Liquid Chromatography and Capillary Electrophoresis both coupled to Mass Spectrometry (LC-MS and CE-MS, respectively). Results showed the osteocyte profile was very similar under SC, regardless of their pre-conditioning treatment, while, after FF stimulation, secretomes followed different metabolic signatures depending on the pre-conditioning treatment. An important increment of citrate pointed out that osteocytes release citrate outside of the cell to induce osteoblast activation, while HG environment impaired FF effect. This study demonstrates for the first time that osteocytes increase citrate excretion under mechanical stimulation, and that HG environment impaired this effect.

Metabolomic and glycomic findings in posttraumatic stress disorder

Posttraumatic stress disorder (PTSD) is a stressor-related disorder that develops in a subset of individuals exposed to a traumatic experience. Factors associated with vulnerability to PTSD are still not fully understood. PTSD is frequently comorbid with various psychiatric and somatic disorders, moderate response to treatment and remission rates. The term "theranostics" combines diagnosis, prognosis, and therapy and offers targeted therapy based on specific analyses. Theranostics, combined with novel techniques and approaches called "omics", which integrate genomics, transcriptomic, proteomics and metabolomics, might improve knowledge about biological underpinning of PTSD, and offer novel therapeutic strategies. The focus of this review is on metabolomic and glycomic data in PTSD. Metabolomics evaluates changes in the metabolome of an organism by exploring the set of small molecules (metabolites), while glycomics studies the glycome, a complete repertoire of glycan structures with their functional roles in biological systems. Both metabolome and glycome reflect the physiological and pathological conditions in individuals. Only a few studies evaluated metabolic and glycomic changes in patients with PTSD. The metabolomics studies in PTSD patients uncovered different metabolites that might be associated with psychopathological alterations in PTSD. The glycomics study in PTSD patients determined nine N-glycan structures and found accelerated and premature aging in traumatized subjects and subjects with PTSD based on a GlycoAge index. Therefore, further larger studies and replications are needed. Better understanding of the biological basis of PTSD, including metabolomic and glycomic data, and their integration with other "omics" approaches, might identify new molecular targets and might provide improved therapeutic approaches.

Balancing metabolome coverage and reproducibility for untargeted NMR-based metabolic profiling in tissue samples through mixture design methods

Untargeted metabolomics attempts to acquire a comprehensive and reproducible set of small-molecule metabolites in biological systems. However, metabolite extraction method significantly affects the quality of metabolomics data. In the present study, we calculated the number of peaks (NP) and coefficient of variation (CV) to reflect metabolome coverage and reproducibility in untargeted NMR-based metabolic profiling of tissue samples in rats under different methanol/chloroform/water (MCW) extraction conditions. Different MCW extractions expectedly generated diverse characteristics of metabolome. Moreover, the classic MCW method revealed tissue-specific differences in the NP and CV values. To obtain high-quality metabolomics data, therefore, we used mixture design methods to optimize the MCW extraction strategy by maximizing the NP value and minimizing the CV value in each tissue sample. Results show that the optimal formulations of MCW extraction were 2:2:8 (ml/mg tissue) for brain sample, 2:4:6 (ml/mg tissue) for heart sample, 1.3:2:8.7 (ml/mg tissue) for liver sample, 4:2:6 (ml/mg tissue) for kidney sample, 2:3:7 (ml/mg tissue) for muscle sample, and 2:4:6 (ml/mg tissue) for pancreas sample. Therefore, these findings demonstrate that different tissue samples need a specific optimal extraction condition for balancing metabolome coverage and reproducibility in the untargeted metabolomics study. Mixture design method is an effective tool to optimize metabolite extraction strategy for tissue samples. Graphical abstract ᅟ.

Metabolomics and Lipidomics Approaches in the Science of Probiotics: A Review

The intestinal microflora plays important roles in the health of the host, such as nutrient processing and the modulation of intestinal immune responses. The constituents of the diet greatly affect the composition of the microbiota and its metabolites. The human intestinal microbiota is made up of around 100 trillion microbial cells encompassing at least 300 species. Consuming probiotics may lead to changes in the intestinal microflora that influence host health. Metabolomics is a powerful tool for revealing metabolic changes in biofluids, tissues, and organs of hosts induced by the consumption of probiotics, and lipidomics in particular is a technical approach that focuses on the analysis of lipids in various cells and biofluids. Metabolomics and lipidomics have been used to investigate intracellular and extracellular metabolites as well as for the nontargeted profiling and fingerprinting of metabolites. Based on metabolomics and lipidomics investigations, we reviewed the effects of consuming probiotics on metabolic profiles in controlled intestinal environments. We also discuss the associations between metabolic changes and human diseases after consuming probiotics in uncontrolled intestinal environments. In addition, we review the metabolic changes that take place within the food matrix during probiotic fermentation.

Effects of Postoperative Parenteral Nutrition Enhanced by Multivitamin on Metabolic Phenotype in Postoperative Gastric Cancer Patients

SCOPE

To investigate the effects of postoperative parenteral nutrition (PN) with multivitamins supplementation on oxidative stress and metabolism.

METHODS AND RESULTS

The participants are randomly assigned in a 1:1 ratio to groups: total nutrient admixture (TNA) + multivitamin (n = 14, Group A) and TNA + normal saline (n = 16, Group B). The levels of blood vitamins, ILs, and MDA are assessed and the dysregulation of metabolism is analyzed using nontargeted metabolite profiling. The degree of postoperative stress in Group A is significantly lower than that in Group B by analyzing changes in the levels of IL-8 and MDA. A set of 43 features are qualified to have a variable importance parameter score of >1.5 of a partial least-squares discriminate analysis model and fold change of >1.5 at p-value <0.05 between Groups A and B. The principal metabolic alternations in Group A include increased tricarboxylic acid cycle and ketogenesis with reduced plasma-free amino acids. Backing the results of clinical biomarkers, increased levels of antioxidative molecules, together with decreased levels of inflammatory related polyunsaturated fatty acids, are observed.

CONCLUSION

Postoperative PN enhanced by multivitamins can alleviate traumatic stress and improve metabolic transition from catabolism to anabolism in gastric cancer patients.

Ferritin H Deficiency in Myeloid Compartments Dysregulates Host Energy Metabolism and Increases Susceptibility to Mycobacterium tuberculosis Infection

Iron is an essential factor for the growth and virulence of Mycobacterium tuberculosis (Mtb). However, little is known about the mechanisms by which the host controls iron availability during infection. Since ferritin heavy chain (FtH) is a major intracellular source of reserve iron in the host, we hypothesized that the lack of FtH would cause dysregulated iron homeostasis to exacerbate TB disease. Therefore, we used knockout mice lacking FtH in myeloid-derived cell populations to study Mtb disease progression. We found that FtH plays a critical role in protecting mice against Mtb, as evidenced by increased organ burden, extrapulmonary dissemination, and decreased survival in Fth-/- mice. Flow cytometry analysis showed that reduced levels of FtH contribute to an excessive inflammatory response to exacerbate disease. Extracellular flux analysis showed that FtH is essential for maintaining bioenergetic homeostasis through oxidative phosphorylation. In support of these findings, RNAseq and mass spectrometry analyses demonstrated an essential role for FtH in mitochondrial function and maintenance of central intermediary metabolism in vivo. Further, we show that FtH deficiency leads to iron dysregulation through the hepcidin-ferroportin axis during infection. To assess the clinical significance of our animal studies, we performed a clinicopathological analysis of iron distribution within human TB lung tissue and showed that Mtb severely disrupts iron homeostasis in distinct microanatomic locations of the human lung. We identified hemorrhage as a major source of metabolically inert iron deposition. Importantly, we observed increased iron levels in human TB lung tissue compared to healthy tissue. Overall, these findings advance our understanding of the link between iron-dependent energy metabolism and immunity and provide new insight into iron distribution within the spectrum of human pulmonary TB. These metabolic mechanisms could serve as the foundation for novel host-directed strategies.

Metabolomic analysis for the protective effects of mangiferin on sepsis-induced lung injury in mice

This study aimed to investigate the efficacy of mangiferin, including its known antioxidant and anti-inflammatory effects on sepsis-induced lung injury induced by a classical cecal ligation and puncture (CLP) models in mouse using a metabolomics approach. A total of 24 mice were randomly divided into four groups: the sham group was given saline before sham operation. The CLP group received the CLP operation only. HMF and LMF groups were given mangiferin treatment of high dose and low dose of mangiferin, respectively, before the CLP operation. One week after treatment, the mice were sacrificed and their lungs were collected for metabolomics analysis. We developed ultra-performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry to perform lung metabolic profiling analysis. With the methods of principal component analysis and partial least squares discriminant analysis, 58 potential metabolites associated with amino acid metabolism, purine metabolism, lipid metabolism and energy regulation were observed to be increased or reduced in HMF and LMF groups compared with the CLP group. Conclusively, our results suggest that mangiferin plays a protective role in the moderation of sepsis-induced lung injury through reducing oxidative stress, regulating lipid metabolism and energy biosynthesis.

Metabolomics: A High-Throughput Platform for Metabolite Profile Exploration

Metabolomics aims to quantitatively measure small-molecule metabolites in biological samples, such as bodily fluids (e.g., urine, blood, and saliva), tissues, and breathe exhalation, which reflects metabolic responses of a living system to pathophysiological stimuli or genetic modification. In the past decade, metabolomics has made notable progresses in providing useful systematic insights into the underlying mechanisms and offering potential biomarkers of many diseases. Metabolomics is a complementary manner of genomics and transcriptomics, and bridges the gap between genotype and phenotype, which reflects the functional output of a biological system interplaying with environmental factors. Recently, the technology of metabolomics study has been developed quickly. This review will discuss the whole pipeline of metabolomics study, including experimental design, sample collection and preparation, sample detection and data analysis, as well as mechanism interpretation, which can help understand metabolic effects and metabolite function for living organism in system level.

Metabolic changes in primary, secondary, and lipid metabolism in tobacco leaf in response to topping

As an important cultivation practice used for flue-cured tobacco, topping affects diverse biological processes in the later stages of development and growth. Some studies have focused on using tobacco genes to reflect the physiological changes caused by topping. However, the complex metabolic shifts in the leaf resulting from topping have not yet been investigated in detail. In this study, a comprehensive metabolic profile of primary, secondary, and lipid metabolism in flue-cured tobacco leaf was generated with use of a multiple platform consisting of gas chromatography-mass spectrometry, capillary electrophoresis-mass spectrometry, and liquid chromatography-mass spectrometry/ultraviolet spectroscopy. A total of 367 metabolites were identified and determined. Both principal component analysis and the number of significantly different metabolites indicated that topping had the greatest influence on the upper leaves. During the early stage of topping, great lipid level variations in the upper leaves were observed, and antioxidant defense metabolites were accumulated. This indicated that the topping activated lipid turnover and the antioxidant defense system. At the mature stage, lower levels of senescence-related metabolites and higher levels of secondary metabolites were found in the topped mature leaves. This implied that topping delayed leaf senescence and promoted secondary metabolite accumulation. This study provides a global view of the metabolic perturbation in response to topping. Graphical abstract Metabolic alterations in tobacco leaf in response to topping using a multiplatform metabolomics.

Short overview on metabolomic approach and redox changes in psychiatric disorders

Schizophrenia, depression and posttraumatic stress disorder (PTSD) are severe mental disorders and complicated diagnostic entities, due to their phenotypic, biological and genetic heterogeneity, unknown etiology, and poorly understood alterations in biological pathways and biological mechanisms. Disturbed homeostasis between overproduction of oxidant species, overcoming redox regulation and a lack of cellular antioxidant defenses, resulting in free radical-mediated pathology and subsequent neurotoxicity contributes to development of depression, schizophrenia and PTSD, their heterogeneous clinical presentation and resistance to treatment. Metabolomics is a discipline that combines different strategies with the aim to extract, detect, identify and quantify all metabolites that are present in a biological sample and might provide mechanistic insights into the etiology of various psychiatric disorders. Therefore, oxidative stress research combined with metabolomics might offer a novel approach in dissecting psychiatric disorders, since these data-driven but not necessarily hypothesis-driven methods might identify new targets, molecules and pathways responsible for development of schizophrenia, depression or PTSD. Findings from the oxidative research in psychiatry together with metabolomics data might facilitate development of specific and validated prognostic, therapeutic and clinical biomarkers. These methods might reveal bio-signatures of individual patients, leading to individualized treatment approach. In reviewing findings related to oxidative stress and metabolomics in selected psychiatric disorders, we have highlighted how these novel approaches might make a unique contribution to deeper understanding of psychopathological alterations underlying schizophrenia, depression and PTSD.

Quality assurance procedures for mass spectrometry untargeted metabolomics. a review

Untargeted metabolomics, as a global approach, has already proven its great potential and capabilities for the investigation of health and disease, as well as the wide applicability for other research areas. Although great progress has been made on the feasibility of metabolomics experiments, there are still some challenges that should be faced and that includes all sources of fluctuations and bias affecting every step involved in multiplatform untargeted metabolomics studies. The identification and reduction of the main sources of unwanted variation regarding the pre-analytical, analytical and post-analytical phase of metabolomics experiments is essential to ensure high data quality. Nowadays, there is still a lack of information regarding harmonized guidelines for quality assurance as those available for targeted analysis. In this review, sources of variations to be considered and minimized along with methodologies and strategies for monitoring and improvement the quality of the results are discussed. The given information is based on evidences from different groups among our own experiences and recommendations for each stage of the metabolomics workflow. The comprehensive overview with tools presented here might serve other researchers interested in monitoring, controlling and improving the reliability of their findings by implementation of good experimental quality practices in the untargeted metabolomics study.

Metabolic and microbial signatures in rat hepatocellular carcinoma treated with caffeic acid and chlorogenic acid

Hepatocellular carcinoma (HCC) treatment remains lack of effective chemopreventive agents, therefore it is very attractive and urgent to discover novel anti-HCC drugs. In the present study, the effects of chlorogenic acid (ChA) and caffeic acid (CaA) on HCC induced by diethylnitrosamine (DEN) were evaluated. ChA or CaA could reduce the histopathological changes and liver injury markers, such as alanine transarninase, aspartate aminotransferase, alkaline phosphatase, total bile acid, total cholesterol, high density lipoprotein cholesterol and low density lipoprotein cholesterol. The underlying mechanisms were investigated by a data integration strategy based on correlation analyses of metabonomics data and 16 S rRNA gene sequencing data. ChA or CaA could inhibit the increase of Rumincoccaceae UCG-004 and reduction of Lachnospiraceae incertae sedis, and Prevotella 9 in HCC rats. The principal component analysis and partial least squares discriminant analysis were applied to reveal the metabolic differences among these groups. 28 different metabolites showed a trend to return to normal in both CaA and ChA treatment. Among them, Bilirubin, L-Tyrosine, L-Methionine and Ethanolamine were correlated increased Rumincoccaceae UCG-004 and decreased of Lachnospiraceae incertae sedis and Prevotella 9. These correlations could be identified as metabolic and microbial signatures of HCC onset and potential therapeutic targets.

Development of LC-QTOF-MS method for human lung tissue fingerprinting. A preliminary application to nonsmall cell lung cancer

The major histologic subtypes of non-small cell lung cancer (NSCLC) include adenocarcinoma (ADC), squamous cell lung carcinoma (SCC), and large-cell carcinoma (LCC). Clinical trials of targeted agents and newer chemotherapy agents yielded differences in outcomes according to histologic subgroups providing a rationale for histology-based treatment in NSCLC. Currently, NSCLC subtyping is performed based on histopathological examinations and immunohistochemistry. However available methods leave about 10% of NSCLC cases as not otherwise specified. The purpose of this study was development of an LC-QTOF-MS method for human lung tissue metabolic fingerprinting that could discriminate NSCLC histological subtypes and propose biomarkers candidates that could support proper NSCLC diagnosis. Metabolites were extracted with acetonitrile or methanol/ethanol and different chromatographic conditions were tested. In the final method 10 mg of lung tissue was homogenized with 50% methanol and metabolites were extracted with acetonitrile. Metabolites were separated on C8-RP and HILIC columns. About 3500 and 2000 of metabolic features (in both ion modes) were detected with good repeatability (CV < 20%) by RP and HILIC methods, respectively. Lung tumor and control tissue samples obtained from NSCLC patients were analyzed with developed methodology. Acylcarnitines, fatty acids, phospholipids, and amino acids were found more abundant in tumor as compared to control tissue. Acylcarnitines, lysophospholipids, creatinine, creatine, and alanine were identified as potential targets enabling classification of NSCLC subtypes.

Metabolomics and neuroanatomical evaluation of post-mortem changes in the hippocampus

Understanding the human brain is the ultimate goal in neuroscience, but this is extremely challenging in part due to the fact that brain tissue obtained from autopsy is practically the only source of normal brain tissue and also since changes at different levels of biological organization (genetic, molecular, biochemical, anatomical) occur after death due to multiple mechanisms. Here we used metabolomic and anatomical techniques to study the possible relationship between post-mortem time (PT)-induced changes that may occur at both the metabolomics and anatomical levels in the same brains. Our experiments have mainly focused on the hippocampus of the mouse. We found significant metabolomic changes at 2 h PT, whereas the integrity of neurons and glia, at the anatomical/ neurochemical level, was not significantly altered during the first 5 h PT for the majority of histological markers.

Metabolomic Fingerprinting in the Comprehensive Study of Liver Changes Associated with Onion Supplementation in Hypercholesterolemic Wistar Rats

The consumption of functional ingredients has been suggested to be a complementary tool for the prevention and management of liver disease. In this light, processed onion can be considered as a source of multiple bioactive compounds with hepatoprotective properties. The liver fingerprint of male Wistar rats (n = 24) fed with three experimental diets (control (C), high-cholesterol (HC), and high-cholesterol enriched with onion (HCO) diets) was obtained through a non-targeted, multiplatform metabolomics approach to produce broad metabolite coverage. LC-MS, CE-MS and GC-MS results were subjected to univariate and multivariate analyses, providing a list of significant metabolites. All data were merged in order to figure out the most relevant metabolites that were modified by the onion ingredient. Several relevant metabolic changes and related metabolic pathways were found to be impacted by both HC and HCO diet. The model highlighted several metabolites (such as hydroxybutyryl carnitine and palmitoyl carnitine) modified by the HCO diet. These findings could suggest potential impairments in the energy−lipid metabolism, perturbations in the tricarboxylic acid cycle (TCA) cycle and β-oxidation modulated by the onion supplementation in the core of hepatic dysfunction. Metabolomics shows to be a valuable tool to evaluate the effects of complementary dietetic approaches directed to hepatic damage amelioration or non-alcoholic fatty liver disease (NAFLD) prevention.

Capillary electrophoresis mass spectrometry as a tool for untargeted metabolomics

Highly polar and ionic metabolites, such as sugars, most amino acids, organic acids or nucleotides are not retained by conventional reversed-phase LC columns and polar stationary phases and hydrophilic-interaction LC lacks of robustness, which is still limiting their applications for untargeted metabolomics where reproducibility is a must. Biological samples such as blood, urine or even tissues include many hydrophilic compounds secreted from cells, their analysis is essential for biomarker discovery, disease progression or treatment effects. This review focuses on CE coupled to MS as a mature technique for untargeted metabolomics including sample pretreatment, types of matrices, analytical methods, applications and data treatment strategies for polar compound analysis in biological matrices. The main applications and results of CE-MS in untargeted metabolomics are discussed and presented in a tabulated format.

Metabolic profiling of ob/ob mouse fatty liver using HR-MAS 1H-NMR combined with gene expression analysis reveals alterations in betaine metabolism and the transsulfuration pathway

Metabolic perturbations resulting from excessive hepatic fat accumulation are poorly understood. Thus, in this study, leptin-deficient ob/ob mice, a mouse model of fatty liver disease, were used to investigate metabolic alterations in more detail. Metabolites were quantified in intact liver tissues of ob/ob (n = 8) and control (n = 8) mice using high-resolution magic angle spinning (HR-MAS) ¹H-NMR. In addition, after demonstrating that HR-MAS ¹H-NMR does not affect RNA integrity, transcriptional changes were measured by quantitative real-time PCR on RNA extracted from the same specimens after HR-MAS ¹H-NMR measurements. Importantly, the gene expression changes obtained agreed with those observed by Affymetrix microarray analysis performed on RNA isolated directly from fresh-frozen tissue. In total, 40 metabolites could be assigned in the spectra and subsequently quantified. Quantification of lactate was also possible after applying a lactate-editing pulse sequence that suppresses the lipid signal, which superimposes the lactate methyl resonance at 1.3 ppm. Significant differences were detected for creatinine, glutamate, glycine, glycolate, trimethylamine-N-oxide, dimethylglycine, ADP, AMP, betaine, phenylalanine, and uridine. Furthermore, alterations in one-carbon metabolism, supported by both metabolic and transcriptional changes, were observed. These included reduced demethylation of betaine to dimethylglycine and the reduced expression of genes coding for transsulfuration pathway enzymes, which appears to preserve methionine levels, but may limit glutathione synthesis. Overall, the combined approach is advantageous as it identifies changes not only at the single gene or metabolite level but also deregulated pathways, thus providing critical insight into changes accompanying fatty liver disease. Graphical abstract A Evaluation of RNA integrity before and after HR-MAS ¹H-NMR of intact mouse liver tissue. B Metabolite concentrations and gene expression levels assessed in ob/ob (steatotic) and ob/+ (control) mice using HR-MAS ¹H-NMR and qRT-PCR, respectively.