Metabolomics by Gas Chromatography-Mass Spectrometry: Combined Targeted and Untargeted Profiling

Ion mobility mass spectrometry in the omics era: Challenges and opportunities for metabolomics and lipidomics

Researchers worldwide are taking advantage of novel, commercially available, technologies, such as ion mobility mass spectrometry (IM-MS), for metabolomics and lipidomics applications in a variety of fields including life, biomedical, and food sciences. IM-MS provides three main technical advantages over traditional LC-MS workflows. Firstly, in addition to mass, IM-MS allows collision cross-section values to be measured for metabolites and lipids, a physicochemical identifier related to the chemical shape of an analyte that increases the confidence of identification. Second, IM-MS increases peak capacity and the signal-to-noise, improving fingerprinting as well as quantification, and better defining the spatial localization of metabolites and lipids in biological and food samples. Third, IM-MS can be coupled with various fragmentation modes, adding new tools to improve structural characterization and molecular annotation. Here, we review the state-of-the-art in IM-MS technologies and approaches utilized to support metabolomics and lipidomics applications and we assess the challenges and opportunities in this growing field.

Seed Imbibition and Metabolism Contribute Differentially to Initial Assembly of the Soybean Holobiont

Seed germination critically determines successful plant establishment and agricultural productivity. In the plant holobiont's life cycle, seeds are hubs for microbial communities' assembly, but what exactly shapes the holobiont during germination remains unknown. Here, 16S rRNA gene amplicon sequencing characterized the bacterial communities in embryonic compartments (cotyledons and axes) and on seed coats pre- and post-germination of four soybean (Glycine max) cultivars, in the presence or absence of exogenous abscisic acid (ABA), which prevented germination and associated metabolism of seeds that had imbibed. Embryonic compartments were metabolically profiled during germination to design minimal media mimicking the seed endosphere for bacterial growth assays. The distinction between embryonic and seed coat bacterial microbiomes of dry seeds weakened during germination, resulting in the plumule, radicle, cotyledon, and seed coat all hosting the same most abundant and structurally influential genera in germinated seeds of every cultivar. Treatment with ABA prevented the increase of bacterial microbiomes' richness, but not taxonomic homogenization across seed compartments. Growth assays on minimal media containing the most abundant metabolites that accumulated in germinated seeds revealed that seed reserve mobilization promoted enrichment of copiotrophic bacteria. Our data show that seed imbibition enabled distribution of seed-coat-derived epiphytes into embryos irrespective of germination, while germinative metabolism promoted proliferation of copiotrophic taxa, which predominated in germinated seeds.

The emerging roles of next-generation metabolomics in critical care nutrition

Critical illness leads to millions of deaths worldwide each year, with a significant surge due to the COVID-19 pandemic. Patients with critical illness are frequently associated with systemic metabolic disorders and malnutrition. The idea of intervention for critically ill patients through enteral and parenteral nutrition has been paid more and more attention gradually. However, current nutritional therapies focus on evidence-based practice, and there have been lacking holistic approaches for nutritional support assessment. Metabolomics is a well-established omics technique in system biology that enables comprehensive profiling of metabolites in a biological system and thus provides the underlying information expressed and modulated by all other omics layers. In recent years, with the development of high-resolution and accurate mass spectrometry, metabolomics entered a new "generation", promoting its broader applications in critical care nutrition. In this review, we first described the technological development and milestones of next-generation metabolomics in the past 20 years. We then discussed the emerging roles of next-generation metabolomics in advancing our understanding of critical care nutrition, such as nutritional deficiency risk evaluation, metabolic mechanisms of nutritional therapies, and novel nutrition target identification.

The histone deacetylases Rpd3 and Hst1 antagonistically regulate de novo NAD+ metabolism in the budding yeast Saccharomyces cerevisiae

NAD⁺ is a cellular redox cofactor involved in many essential processes. The regulation of NAD⁺ metabolism and the signaling networks reciprocally interacting with NAD⁺-producing metabolic pathways are not yet fully understood. The NAD⁺-dependent histone deacetylase (HDAC) Hst1 has been shown to inhibit de novo NAD⁺ synthesis by repressing biosynthesis of nicotinic acid (BNA) gene expression. Here, we alternatively identify HDAC Rpd3 as a positive regulator of de novo NAD⁺ metabolism in the budding yeast Saccharomyces cerevisiae. We reveal that deletion of RPD3 causes marked decreases in the production of de novo pathway metabolites, in direct contrast to deletion of HST1. We determined the BNA expression profiles of rpd3Δ and hst1Δ cells to be similarly opposed, suggesting the two HDACs may regulate the BNA genes in an antagonistic fashion. Our chromatin immunoprecipitation analysis revealed that Rpd3 and Hst1 mutually influence each other’s binding distribution at the BNA2 promoter. We demonstrate Hst1 to be the main deacetylase active at the BNA2 promoter, with hst1Δ cells displaying increased acetylation of the N-terminal tail lysine residues of histone H4, H4K5, and H4K12. Conversely, we show that deletion of RPD3 reduces the acetylation of these residues in an Hst1-dependent manner. This suggests that Rpd3 may function to oppose spreading of Hst1-dependent heterochromatin and represents a unique form of antagonism between HDACs in regulating gene expression. Moreover, we found that Rpd3 and Hst1 also coregulate additional targets involved in other branches of NAD⁺ metabolism. These findings help elucidate the complex interconnections involved in effecting the regulation of NAD⁺ metabolism.

Metabolomics of Human Semen: A Review of Different Analytical Methods to Unravel Biomarkers for Male Fertility Disorders

Background: Human life without sperm is not possible. Therefore, it is alarming that the fertilizing ability of human spermatozoa is continuously decreasing. The reasons for that are widely unknown, but there is hope that metabolomics-based investigations may be able to contribute to overcoming this problem. This review summarizes the attempts made so far. Methods: We will discuss liquid chromatography–mass spectrometry (LC-MS), gas chromatography (GC), infrared (IR) and Raman as well as nuclear magnetic resonance (NMR) spectroscopy. Almost all available studies apply one of these methods. Results: Depending on the methodology used, different compounds can be detected, which is (in combination with sophisticated methods of bioinformatics) helpful to estimate the state of the sperm. Often, but not in all cases, there is a correlation with clinical parameters such as the sperm mobility. Conclusions: LC-MS detects the highest number of metabolites and can be considered as the method of choice. Unfortunately, the reproducibility of some studies is poor, and, thus, further improvements of the study designs are needed to overcome this problem. Additionally, a stronger focus on the biochemical consequences of the altered metabolite concentrations is also required.

Methods to capture proteomic and metabolomic signatures from cerebrospinal fluid and serum of healthy individuals

Discovery of reliable signatures for the empirical diagnosis of neurological diseases-both infectious and non-infectious-remains unrealized. One of the primary challenges encountered in such studies is the lack of a comprehensive database representative of a signature background that exists in healthy individuals, and against which an aberrant event can be assessed. For neurological insults and injuries, it is important to understand the normal profile in the neuronal (cerebrospinal fluid) and systemic fluids (e.g., blood). Here, we present the first comparative multi-omic human database of signatures derived from a population of 30 individuals (15 males, 15 females, 23-74 years) of serum and cerebrospinal fluid. In addition to empirical signatures, we also assigned common pathways between serum and CSF. Together, our findings provide a cohort against which aberrant signature profiles in individuals with neurological injuries/disease can be assessed-providing a pathway for comprehensive diagnostics and therapeutics discovery.

Predictive Metabolomic Markers in Early to Mid-pregnancy for Gestational Diabetes Mellitus: A Prospective Test and Validation Study

Gestational diabetes mellitus (GDM) predisposes pregnant individuals to perinatal complications and long-term diabetes and cardiovascular diseases. We developed and validated metabolomic markers for GDM in a prospective test-validation study. In a case-control sample within the PETALS cohort (GDM n = 91 and non-GDM n = 180; discovery set), a random PETALS subsample (GDM n = 42 and non-GDM n = 372; validation set 1), and a case-control sample within the GLOW trial (GDM n = 35 and non-GDM n = 70; validation set 2), fasting serum untargeted metabolomics were measured by gas chromatography/time-of-flight mass spectrometry. Multivariate enrichment analysis examined associations between metabolites and GDM. Ten-fold cross-validated LASSO regression identified predictive metabolomic markers at gestational weeks (GW) 10-13 and 16-19 for GDM. Purinone metabolites at GW 10-13 and 16-19 and amino acids, amino alcohols, hexoses, indoles, and pyrimidine metabolites at GW 16-19 were positively associated with GDM risk (false discovery rate <0.05). A 17-metabolite panel at GW 10-13 outperformed the model using conventional risk factors, including fasting glycemia (area under the curve: discovery 0.871 vs. 0.742, validation 1 0.869 vs. 0.731, and validation 2 0.972 vs. 0.742; P < 0.01). Similar results were observed with a 13-metabolite panel at GW 17-19. Dysmetabolism is present early in pregnancy among individuals progressing to GDM. Multimetabolite panels in early pregnancy can predict GDM risk beyond conventional risk factors.

Iron Deficiency and Overload Modulate the Inflammatory Responses and Metabolism of Alveolar Macrophages

Alveolar macrophages (AM) are critical to defense against respiratory pathogens. This study evaluated cellular iron imbalance to immunometabolism in endotoxin-polarized porcine AMs (PAMs). PAMs collected from five 6-week-old pigs were treated with a basal media, iron chelator, or ferric ammonium citrate to maintain iron replete or induce iron deficiency or overload, respectively. After 24 h treatment, PAMs were challenged with saline or lipopolysaccharide (LPS) for 6 h. Cells were analyzed for gene, protein, and untargeted metabolome. Cytokines were determined in culture media. Data were assessed using two-way ANOVA. Treatments successfully induced iron deficiency and overload. The mRNA of DMT1 and ZIP14 was increased up to 300-fold by LPS, but unaffected by iron. Surprisingly, both iron deprivation and overload attenuated LPS-induced inflammation, showing less TNFα production and lower mRNA of pro- and anti-inflammatory cytokines than iron-replete PAMs. Forty-eight metabolites were altered by either or both main effects. LPS enhanced the glycolysis and polyol pathways. Iron deprivation disrupted the TCA cycle. Iron overload increased intracellular cholesterol. Interestingly, iron deprivation augmented, whereas iron overload diminished, LPS-induced itaconic acid production, which has anti-microbial and anti-inflammatory properties. Therefore, iron-deficient PAMs may be more resistant to intracellular pathogens which use PAMs as a conduit for infection.

Styrylpyrone Derivative (SPD) Extracted from Goniothalamus umbrosus Binds to Dengue Virus Serotype-2 Envelope Protein and Inhibits Early Stage of Virus Replication

A study was conducted to investigate the anti-viral effect of a styrylpyrone derivative (SPD) called goniothalamin and the effects on the dengue virus serotype 2 (DENV-2) replication cycle. The SPD was prepared from the root of Goniothalamus umbrosus after purification with petroleum ether. The isolated SPD was then subjected to gas chromatography–mass spectrometry (GC-MS) and nuclear magnetic resonance (NMR) analyses for structure validation. The cytotoxicity of the SPD was evaluated using a cell viability assay, while the anti-viral activity of the SPD towards DENV-2 was confirmed by conducting a foci reduction assay which involved virus yield reduction, time-of-addition, and time removal assays. Transcriptomic analysis via quantitative real-time polymerase chain reaction (qRT-PCR) using the DENV-2 E gene was conducted to investigate the level of gene transcript. Immunocytochemistry analysis was used to investigate the effects of SPD treatment on protein E expression. Finally, software molecular docking of the SPD and E protein was also performed. The cytotoxicity assay confirmed that the SPD was not toxic to Vero cells, even at the highest concentration tested. In the time-of-addition assay, more than 80% foci reduction was observed when SPDs were administered at 2 h post-infection (hpi), and the reduction percentage then dropped with the delay of the treatment time, suggesting the inhibition of the early replication cycle. However, the time removal assay showed that more than 80% reduction could only be observed after 96 h post-treatment with the SPD. Treatment with the SPD reduced the progeny infectivity when treated for 24 h and was dose-dependent. The result showed that transcript level of the E gene in infected cells treated with the SPD was reduced compared to infected cells without treatment. In immunocytochemistry analysis, the DENV-2 E protein exhibited similar expression trends, shown by the gene transcription level. Molecular docking showed that the SPD can interact with E protein through hydrogen bonds and other interactions. Overall, this study showed that SPDs have the potential to be anti-DENV-2 via a reduction in viral progeny infectivity and a reduction in the expression of the DENV-2 E gene and protein at different phases of viral replication. SPDs should be further researched to be developed into an effective anti-viral treatment, particularly for early-phase dengue viral infection.

Metabolomic Evidence for Peroxisomal Dysfunction in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic and debilitating disease characterized by unexplained physical fatigue, cognitive and sensory dysfunction, sleeping disturbances, orthostatic intolerance, and gastrointestinal problems. People with ME/CFS often report a prodrome consistent with infections. Using regression, Bayesian and enrichment analyses, we conducted targeted and untargeted metabolomic analysis of plasma from 106 ME/CFS cases and 91 frequency-matched healthy controls. Subjects in the ME/CFS group had significantly decreased levels of plasmalogens and phospholipid ethers (p < 0.001), phosphatidylcholines (p < 0.001) and sphingomyelins (p < 0.001), and elevated levels of dicarboxylic acids (p = 0.013). Using machine learning algorithms, we were able to differentiate ME/CFS or subgroups of ME/CFS from controls with area under the receiver operating characteristic curve (AUC) values up to 0.873. Our findings provide the first metabolomic evidence of peroxisomal dysfunction, and are consistent with dysregulation of lipid remodeling and the tricarboxylic acid cycle. These findings, if validated in other cohorts, could provide new insights into the pathogenesis of ME/CFS and highlight the potential use of the plasma metabolome as a source of biomarkers for the disease.

Non-Targeted Metabolomics Approach Revealed Significant Changes in Metabolic Pathways in Patients with Chronic Traumatic Encephalopathy

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease that is frequently found in athletes and those who have experienced repetitive head traumas. CTE is associated with a variety of neuropathologies, which cause cognitive and behavioral impairments in CTE patients. However, currently, CTE can only be diagnosed after death via brain autopsy, and it is challenging to distinguish it from other neurodegenerative diseases with similar clinical features. To better understand this multifaceted disease and identify metabolic differences in the postmortem brain tissues of CTE patients and control subjects, we performed ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS)-based non-targeted metabolomics. Through multivariate and pathway analysis, we found that the brains of CTE patients had significant changes in the metabolites involved in astrocyte activation, phenylalanine, and tyrosine metabolism. The unique metabolic characteristics of CTE identified in this study were associated with cognitive dysfunction, amyloid-beta deposition, and neuroinflammation. Altogether, this study provided new insights into the pathogenesis of CTE and suggested appealing targets for both diagnosis and treatment for the disease.

Integration of Infant Metabolite, Genetic, and Islet Autoimmunity Signatures to Predict Type 1 Diabetes by Age 6 Years

CONTEXT

Biomarkers that can accurately predict risk of type 1 diabetes (T1D) in genetically predisposed children can facilitate interventions to delay or prevent the disease.

OBJECTIVE

This work aimed to determine if a combination of genetic, immunologic, and metabolic features, measured at infancy, can be used to predict the likelihood that a child will develop T1D by age 6 years.

METHODS

Newborns with human leukocyte antigen (HLA) typing were enrolled in the prospective birth cohort of The Environmental Determinants of Diabetes in the Young (TEDDY). TEDDY ascertained children in Finland, Germany, Sweden, and the United States. TEDDY children were either from the general population or from families with T1D with an HLA genotype associated with T1D specific to TEDDY eligibility criteria. From the TEDDY cohort there were 702 children will all data sources measured at ages 3, 6, and 9 months, 11.4% of whom progressed to T1D by age 6 years. The main outcome measure was a diagnosis of T1D as diagnosed by American Diabetes Association criteria.

RESULTS

Machine learning-based feature selection yielded classifiers based on disparate demographic, immunologic, genetic, and metabolite features. The accuracy of the model using all available data evaluated by the area under a receiver operating characteristic curve is 0.84. Reducing to only 3- and 9-month measurements did not reduce the area under the curve significantly. Metabolomics had the largest value when evaluating the accuracy at a low false-positive rate.

CONCLUSION

The metabolite features identified as important for progression to T1D by age 6 years point to altered sugar metabolism in infancy. Integrating this information with classic risk factors improves prediction of the progression to T1D in early childhood.

Metabolomics: A New Approach in the Evaluation of Effects in Human Beings and Wildlife Associated with Environmental Exposition to POPs

Human beings and wild organisms are exposed daily to a broad range of environmental stressors. Among them are the persistent organic pollutants that can trigger adverse effects on these organisms due to their toxicity properties. There is evidence that metabolomics can be used to identify biomarkers of effect by altering the profiles of endogenous metabolites in biological fluids or tissues. This approach is relatively new and has been used in vitro studies mainly. Therefore, this review addresses those that have used metabolomics as a key tool to identify metabolites associated with environmental exposure to POPs in wildlife and human populations and that can be used as biomarkers of effect. The published results suggest that the metabolic pathways that produce energy, fatty acids, and amino acids are commonly affected by POPs. Furthermore, these pathways can be promoters of additional effects. In the future, metabolomics combined with other omics will improve understanding of the origin, development, and progression of the effects caused by environmental exposure.

Methodological Developments for Metabolic NMR Spectroscopy from Cultured Cells to Tissue Extracts: Achievements, Progress and Pitfalls

This is a broad overview and critical review of a particular group of closely related ex vivo and in vitro metabolic NMR spectroscopic methods. The scope of interest comprises studies of cultured cells and excised tissue, either intact or after physicochemical extraction of metabolites. Our detailed discussion includes pitfalls that have led to erroneous statements in the published literature, some of which may cause serious problems in metabolic and biological interpretation of results. To cover a wide range of work from relevant research areas, we consider not only the most recent achievements in the field, but also techniques that proved to be valid and successful in the past, although they may not have generated a very significant number of papers more recently. Thus, this comparative review also aims at providing background information useful for judiciously choosing between the metabolic ex vivo/in vitro NMR methods presented. Finally, the methods of interest are discussed in the context of, and in relation to, other metabolic analysis protocols such as HR-MAS and cell perfusion NMR, as well as the mass spectrometry approach.

Early Serum Metabolism Profile of Post-operative Delirium in Elderly Patients Following Cardiac Surgery With Cardiopulmonary Bypass

Background

Cardiac surgery with cardiopulmonary bypass (CPB) is considered to be one of the surgical types with the highest incidence of post-operative delirium (POD). POD has been associated with a prolonged intensive care and hospital stay, long-term neurocognitive deterioration, and increased mortality. However, the specific pathogenesis of POD is still unclear. Untargeted metabolomics techniques can be used to understand the changes of serum metabolites in early POD to discover the relationship between serum metabolites and disease.

Materials and Methods

The present study recruited 58 elderly patients undergoing cardiac surgery with CPB. Serum was collected within the first 24 h after surgery. The Confusion Assessment Method (CAM) and ICU-CAM assessments were used to identify patients who experienced POD. All patients with normal post-operative cognitive assessment were included in the non-POD groups. Moreover, we collected serum from 20 healthy adult volunteers. We performed untargeted analyses of post-operative serum metabolites in all surgical groups, as well as serum metabolites in healthy non-surgical adults by using liquid chromatography mass spectrometry (LC/MS) and analyzed metabolic profiles and related metabolites.

Results

The probability of POD after cardiac surgery were 31%. There were statistically significant differences in post-operative mechanical ventilation time, ICU stay time and post-operative hospital stay between POD and non-POD group (P < 0.05). And ICU stay time was an independent risk factor for POD. The analysis revealed that a total of 51 differentially expressed metabolites (DEMs) were identified by comparing the POD and non-POD group, mostly lipids and lipid-like molecules. Three phosphatidylinositol (PI) were down-regulated in POD group, i.e., PI [18:0/18:2 (9Z, 12Z)], PI [20:4 (8Z, 11Z, 14Z, 17Z)/18:0], and PI [18:1 (9Z)/20:3 (8Z, 11Z, 14Z)]. The receiver operating characteristic (ROC) curve analysis showed that three kinds of PI metabolites had the highest area under the curve (AUC), which were 0.789, 0.781, and 0.715, respectively. Correlation analysis showed that the expression of three PIs was negatively correlated with the incidence of POD.

Conclusion

Our findings suggest that lipid metabolism plays an important role in the serum metabolic profile of elderly patients with POD in the early post-operative period. Low serum lipid metabolic PI was associated with incidence of POD in elderly following cardiac bypass surgery, which may provide new insights into the pathogenesis of POD.

Comprehensive evaluation of caloric restriction-induced changes in the metabolome profile of mice

OBJECTS

Caloric restriction (CR) is known to extend lifespan and exert a protective effect on organs, and is thus a low-cost and easily implemented approach to the health maintenance. However, there have been no studies that have systematically evaluated the metabolic changes that occur in the main tissues affected by CR. This study aimed to explore the target tissues metabolomic profile in CR mice.

METHODS

Male C57BL/6J mice were randomly allocated to the CR group (n = 7) and control group (n = 7). A non-targeted gas chromatography-mass spectrometry approach and multivariate analysis were used to identify metabolites in the main tissues (serum, heart, liver, kidney, cortex, hippocampus, lung, muscle, and white adipose) in model of CR.

RESULTS

We identified 10 metabolites in the heart that showed differential abundance between the 2 groups, along with 9 in kidney, 6 in liver, 6 in lung, 6 in white adipose, 4 in hippocampus, 4 in serum, 3 in cortex, and 2 in muscle. The most significantly altered metabolites were amino acids (AAs) (glycine, aspartic acid, L-isoleucine, L-proline, L-aspartic acid, L-serine, L-hydroxyproline, L-alanine, L-valine, L-threonine, L-glutamic acid, and L-phenylalanine) and fatty acids (FAs) (palmitic acid, 1-monopalmitin, glycerol monostearate, docosahexaenoic acid, 16-octadecenoic acid, oleic acid, stearic acid, and hexanoic acid). These metabolites were associated with 7 different functional pathways related to the metabolism of AAs, lipids, and energy.

CONCLUSION

Our results provide insight into the specific metabolic changes that are induced by CR and can serve as a reference for physiologic studies on how CR improves health and extends lifespan.

The metabolome of Mexican cavefish shows a convergent signature highlighting sugar, antioxidant, and Ageing-Related metabolites

Insights from organisms, which have evolved natural strategies for promoting survivability under extreme environmental pressures, may help guide future research into novel approaches for enhancing human longevity. The cave-adapted Mexican tetra, Astyanax mexicanus, has attracted interest as a model system for metabolic resilience, a term we use to denote the property of maintaining health and longevity under conditions that would be highly deleterious in other organisms (Figure 1). Cave-dwelling populations of Mexican tetra exhibit elevated blood glucose, insulin resistance and hypertrophic visceral adipocytes compared to surface-dwelling counterparts. However, cavefish appear to avoid pathologies typically associated with these conditions, such as accumulation of advanced-glycation-end-products (AGEs) and chronic tissue inflammation. The metabolic strategies underlying the resilience properties of A. mexicanus cavefish, and how they relate to environmental challenges of the cave environment, are poorly understood. Here, we provide an untargeted metabolomics study of long- and short-term fasting in two A. mexicanus cave populations and one surface population. We find that, although the metabolome of cavefish bears many similarities with pathological conditions such as metabolic syndrome, cavefish also exhibit features not commonly associated with a pathological condition, and in some cases considered indicative of an overall robust metabolic condition. These include a reduction in cholesteryl esters and intermediates of protein glycation, and an increase in antioxidants and metabolites associated with hypoxia and longevity. This work suggests that certain metabolic features associated with human pathologies are either not intrinsically harmful, or can be counteracted by reciprocal adaptations. We provide a transparent pipeline for reproducing our analysis and a Shiny app for other researchers to explore and visualize our dataset.

Plasma Metabolite Response to Simple, Refined and Unrefined Carbohydrate-Enriched Diets in Older Adults-Randomized Controlled Crossover Trial

Food intake data collected using subjective tools are prone to inaccuracies and biases. An objective assessment of food intake, such as metabolomic profiling, may offer a more accurate method if unique metabolites can be identified. To explore this option, we used samples generated from a randomized and controlled cross-over trial during which participants (N = 10; 65 ± 8 year, BMI, 29.8 ± 3.2 kg/m²) consumed each of the three diets enriched in different types of carbohydrate. Plasma metabolite concentrations were measured at the end of each diet phase using gas chromatography/time-of-flight mass spectrometry and ultra-high pressure liquid chromatography/quadrupole time-of-flight tandem mass spectrometry. Participants were provided, in random order, with diets enriched in three carbohydrate types (simple carbohydrate (SC), refined carbohydrate (RC) and unrefined carbohydrate (URC)) for 4.5 weeks per phase and separated by two-week washout periods. Data were analyzed using partial least square-discrimination analysis, receiver operating characteristics (ROC curve) and hierarchical analysis. Among the known metabolites, 3-methylhistidine, phenylethylamine, cysteine, betaine and pipecolic acid were identified as biomarkers in the URC diet compared to the RC diet, and the later three metabolites were differentiated and compared to SC diet. Hierarchical analysis indicated that the plasma metabolites at the end of each diet phase were more strongly clustered by the participant than the carbohydrate type. Hence, although differences in plasma metabolite concentrations were observed after participants consumed diets differing in carbohydrate type, individual variation was a stronger predictor of plasma metabolite concentrations than dietary carbohydrate type. These findings limited the potential of metabolic profiling to address this variable.

Community metabolomics provides insights into mechanisms of pollution-induced community tolerance of periphyton

Chemical pollution is a major concern for freshwater ecosystems, but the impact and mechanisms of chemical stressors on communities are barely understood. Pollution stress beyond natural homeostatic capacities can trigger succession of tolerant species within a community, enhancing the overall community tolerance. This process was operationalized in the Pollution-Induced Community Tolerance (PICT) concept and applied in many case studies, however, the molecular mechanisms of community tolerance and implications for ecological functions remain largely unexplored. Our study aimed to demonstrate that 1) community metabolomics can unravel potential mechanisms of PICT in periphyton and 2) induced tolerance helps to maintain primary production under re-occuring pollution. To this end, we grew periphyton for 5 weeks with and without the model herbicide diuron in microcosms, quantified PICT, and determined the related metabolic fingerprint of periphyton by GC-MS-based untargeted metabolomics. Further, we explored the autotrophic community based on pigment composition and functional parameters including photosynthesis and gross primary production. Chronic diuron exposure resulted in a shift in pigment composition, higher community tolerance and an individual metabolic fingerprint in the contaminated communities. Opposing responses of selected metabolites during a short-term exposure indicated differences in diuron pre-adaptation in the different communities. Metabolites (threonic acid and two sugar acid lactones) were found to be related to tolerance development, suggesting that ascorbate metabolism was induced in contaminated communities. Despite these compensating mechanism, contaminated communities were compromised in production-to-respiration ratio and biomass. A ranking of sensitivity thresholds of different biological endpoints revealed that metabolites were less sensitive than photosynthetic parameters, which reflects the mode-of-action of the herbicide. In conclusion, we could demonstrate that community metabolomics is able to unravel complex biochemical changes and allows mechanistic insights into community tolerance. Moreover, we were able to show that induced community tolerance was insufficient to safeguard functions like primary production.

Tissue-Specific Downregulation of Fatty Acid Synthase Suppresses Intestinal Adenoma Formation via Coordinated Reprograming of Transcriptome and Metabolism in the Mouse Model of Apc-Driven Colorectal Cancer

Altered lipid metabolism is a potential target for therapeutic intervention in cancer. Overexpression of Fatty Acid Synthase (FASN) correlates with poor prognosis in colorectal cancer (CRC). While multiple studies show that upregulation of lipogenesis is critically important for CRC progression, the contribution of FASN to CRC initiation is poorly understood. We utilize a C57BL/6-Apc/Villin-Cre mouse model with knockout of FASN in intestinal epithelial cells to show that the heterozygous deletion of FASN increases mouse survival and decreases the number of intestinal adenomas. Using RNA-Seq and gene set enrichment analysis, we demonstrate that a decrease in FASN expression is associated with inhibition of pathways involved in cellular proliferation, energy production, and CRC progression. Metabolic and reverse phase protein array analyses demonstrate consistent changes in alteration of metabolic pathways involved in both anabolism and energy production. Downregulation of FASN expression reduces the levels of metabolites within glycolysis and tricarboxylic acid cycle with the most significant reduction in the level of citrate, a master metabolite, which enhances ATP production and fuels anabolic pathways. In summary, we demonstrate the critical importance of FASN during CRC initiation. These findings suggest that targeting FASN is a potential therapeutic approach for early stages of CRC or as a preventive strategy for this disease.

Utilising lipid and, arginine and proline metabolism in blood plasma to differentiate the biochemical expression in functional dyspepsia (FD) and irritable bowel syndrome (IBS)

Functional gastrointestinal disorders (FGID) such as functional dyspepsia (FD) and irritable bowel syndrome (IBS) are highly prevalent and debilitating attributed to altered gut function and gut-brain interactions. FGID can be reliably diagnosed based upon the symptom pattern; but in the clinical setting FD or IBS a frequent diagnoses of exclusion after relevant structural causes of symptoms have been ruled out by appropriate testing. Thus far, there is no established biomarker for FGIDs. To address this limitation, we utilised multi-omics and chemometrics integration to characterise the blood plasma biochemistry in patients with IBS, FD, an overlap of FD/IBS, and controls using liquid chromatography-mass spectrometry (LC-MS) techniques.Cholesterol metabolism products Cholest-5,24-dien-3β-ol, 3-O-β-D-glucopyranoside, energy pathway metabolites, immunoglobulin-γ2 and immunoglobulin-κ, and carbonic anhydrase-1 proteins were particularly elevated in IBS. Furthermore, arginine and proline metabolisms, thyroid hormone synthesis, ferroptosis and, complementary and coagulation cascades were particularly upregulated in patients with IBS. Cer(d18:1/26:1(17Z)) and PI(14:0/22:1(11Z)) lipids were elevated in FD and FD-IBS but were depleted in IBS. Markers of central carbon metabolism and lipidome profiles allowed better discrimination and model predictability than metaproteome profile in healthy and FGID conditions.Overall, the multi-omics integration allowed the discrimination of healthy controls and FGID patients. It also effectively differentiated the biochemistry of FGID subtypes including FD, IBS and FD-IBS co-occurrence. This study points towards the possibility of multi-omics integration for rapid and high throughput analysis of plasma samples to support clinicians screen and diagnose patients with suspected FGIDs.

Alterations in Blood Plasma Metabolome of Patients with Lesniowski-Crohn's Disease Shortly after Surgical Treatment-Pilot Study

Lesniowski-Crohn’s disease (CD) is a type of chronic inflammatory bowel disease (IBD) of uncertain etiology. Initially, pharmacological management is undertaken; however, surgical intervention is necessary to improve life quality and relieve symptoms in most cases. Here changes are reported in blood metabolome that occurred three days after the ileo-colic region resection in the case of seven patients. Alterations are observed in levels of metabolites associated with multiple mitochondrial pathways, based on the Metabolite Set Enrichment Analysis, reflecting a high energy demand in the post-operative period. As most of these metabolites are also essential nutrients supplied from foods, we believe that our results might contribute to the discussion on perioperative nutrition’s role in enhanced recovery.

Reprogramming of Plant Central Metabolism in Response to Abiotic Stresses: A Metabolomics View

Abiotic stresses rewire plant central metabolism to maintain metabolic and energy homeostasis. Metabolites involved in the plant central metabolic network serve as a hub for regulating carbon and energy metabolism under various stress conditions. In this review, we introduce recent metabolomics techniques used to investigate the dynamics of metabolic responses to abiotic stresses and analyze the trend of publications in this field. We provide an updated overview of the changing patterns in central metabolic pathways related to the metabolic responses to common stresses, including flooding, drought, cold, heat, and salinity. We extensively review the common and unique metabolic changes in central metabolism in response to major abiotic stresses. Finally, we discuss the challenges and some emerging insights in the future application of metabolomics to study plant responses to abiotic stresses.

Gas chromatography-mass spectrometry-based untargeted metabolomics reveals metabolic perturbations in medullary thyroid carcinoma

Medullary thyroid cancer (MTC) is a rare tumor that arises from parafollicular cells within the thyroid gland. The molecular mechanism underlying MTC has not yet been fully understood. Here, we aimed to perform plasma metabolomics profiling of MTC patients to explore the perturbation of metabolic pathways contributing to MTC tumorigenesis. Plasma samples from 20 MTC patients and 20 healthy subjects were obtained to carry out an untargeted metabolomics by gas chromatography–mass spectrometry. Multivariate and univariate analyses were employed as diagnostic tools via MetaboAnalyst and SIMCA software. A total of 76 features were structurally annotated; among them, 13 metabolites were selected to be differentially expressed in MTC patients compared to controls (P < 0.05). These metabolites were mainly associated with the biosynthesis of unsaturated fatty acids and amino acid metabolisms, mostly leucine, glutamine, and glutamate, tightly responsible for tumor cells' energy production. Moreover, according to the receiver operating characteristic curve analysis, metabolites with the area under the curve (AUC) value up to 0.90, including linoleic acid (AUC = 0.935), linolenic acid (AUC = 0.92), and leucine (AUC = 0.948) could discriminate MTC from healthy individuals. This preliminary work contributes to existing knowledge of MTC metabolism by providing evidence of a distinctive metabolic profile in MTC patients relying on the metabolomics approach.

Identification of Secondary Metabolites from Mexican Plants with Antifungal Activity against Pathogenic Candida Species

In the last three decades, invasive fungal infections caused by Candida species have become an important public health problem, because they are associated with high rates of morbidity and mortality in immunocompromised and hospitalized patients. The diagnosis and treatment of candidiasis are difficult and usually inefficient. Accordingly, a diversity of available drugs, currently employed to attack candidiasis, frequently induce resistance in patients promoting toxicity due to long-term treatments. Therefore, development of accurate diagnoses and novel antifungals is of high priority to improve life’s quality and expectancy of individuals infected with this pathogen. Plants are invaluable sources of new biologically active compounds. Among the plants used in Mexico in traditional herbolary medicine which have empirically been demonstrated to have antifungal activity are Pedilanthus tithymaloides, Thymus vulgaris, and Ocimum basilicum. In the present study, we analyzed whether these plants contain metabolites with antifungal activity against five Candida species. The extracts from the different plant organs were obtained by macerating them in ethyl alcohol or hexane and filtering. The obtained extracts were preserved in amber flasks at 4°C until used. The minimum inhibitory concentrations (MICs) of the active compound were determined by a microdilution assay. In addition, the following secondary metabolites were identified: linalool (3,7-dimethylocta-1,6-dien-3-ol), eugenol (4-allyl-2-methoxyphenol), limonene (1-methyl-4-(1-methylethenyl)-cyclohexene), and borneol ([(2R)-1,7,7-trimethyl-2-bicyclo[2.2.1]heptanyl] formate). All these compounds were found in the three plants, traditionally used in everyday life, and proved to be effective against Candida species and therefore a viable alternative to conventional antifungals.

Multiple metabolic pathways fuel the truncated tricarboxylic acid cycle of the prostate to sustain constant citrate production and secretion

Objective

The prostate is metabolically unique: it produces high levels of citrate for secretion via a truncated tricarboxylic acid (TCA) cycle to maintain male fertility. In prostate cancer (PCa), this phenotype is reprogrammed, making it an interesting therapeutic target. However, how the truncated prostate TCA cycle works is still not completely understood.

Methods

We optimized targeted metabolomics in mouse and human organoid models in ex vivo primary culture. We then used stable isotope tracer analyses to identify the pathways that fuel citrate synthesis.

Results

First, mouse and human organoids were shown to recapitulate the unique citrate-secretory program of the prostate, thus representing a novel model that reproduces this unusual metabolic profile. Using stable isotope tracer analysis, several key nutrients were shown to allow the completion of the prostate TCA cycle, revealing a much more complex metabolic profile than originally anticipated. Indeed, along with the known pathway of aspartate replenishing oxaloacetate, glutamine was shown to fuel citrate synthesis through both glutaminolysis and reductive carboxylation in a GLS1-dependent manner. In human organoids, aspartate entered the TCA cycle at the malate entry point, upstream of oxaloacetate. Our results demonstrate that the citrate-secretory phenotype of prostate organoids is supported by the known aspartate–oxaloacetate–citrate pathway, but also by at least three additional pathways: glutaminolysis, reductive carboxylation, and aspartate–malate conversion.

Conclusions

Our results add a significant new dimension to the prostate citrate-secretory phenotype, with at least four distinct pathways being involved in citrate synthesis. Better understanding this distinctive citrate metabolic program will have applications in both male fertility as well as in the development of novel targeted anti-metabolic therapies for PCa.

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Targeted metabolomics and stable isotope tracer analysis were optimized in mouse and human prostate organoids.

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Organoids recapitulate the unique citrate-secretory phenotype of the prostate.

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Glutamine fuels citrate synthesis for secretion by glutaminolysis and reductive carboxylation.

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Aspartate enters the TCA cycle at different entry points in mouse and human prostate organoids for citrate production.

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We revealed a much more complex TCA cycle in the prostate than originally anticipated.

Metabolomic and inflammatory signatures of symptom dimensions in major depression

BACKGROUND

Major depressive disorder (MDD) is a highly heterogenous disease, both in terms of clinical profiles and pathobiological alterations. Recently, immunometabolic dysregulations were shown to be correlated with atypical, energy-related symptoms but less so with the Melancholic or Anxious distress symptom dimensions of depression in The Netherlands Study of Depression and Anxiety (NESDA) study. In this study, we aimed to replicate these immunometabolic associations and to characterize the metabolomic correlates of each of the three MDD dimensions.

METHODS

Using three clinical rating scales, Melancholic, and Anxious distress, and Immunometabolic (IMD) dimensions were characterized in 158 patients who participated in the Predictors of Remission to Individual and Combined Treatments (PReDICT) study and from whom plasma and serum samples were available. The NESDA-defined inflammatory index, a composite measure of interleukin-6 and C-reactive protein, was measured from pre-treatment plasma samples and a metabolomic profile was defined using serum samples analyzed on three metabolomics platforms targeting fatty acids and complex lipids, amino acids, acylcarnitines, and gut microbiome-derived metabolites among other metabolites of central metabolism.

RESULTS

The IMD clinical dimension and the inflammatory index were positively correlated (r = 0.19, p = 0.019) after controlling for age, sex, and body mass index, whereas the Melancholic and Anxious distress dimensions were not, replicating the previous NESDA findings. The three symptom dimensions had distinct metabolomic signatures using both univariate and set enrichment statistics. IMD severity correlated mainly with gut-derived metabolites and a few acylcarnitines and long chain saturated free fatty acids. Melancholia severity was significantly correlated with several phosphatidylcholines, primarily the ether-linked variety, lysophosphatidylcholines, as well as several amino acids. Anxious distress severity correlated with several medium and long chain free fatty acids, both saturated and polyunsaturated ones, sphingomyelins, as well as several amino acids and bile acids.

CONCLUSION

The IMD dimension of depression appears reliably associated with markers of inflammation. Metabolomics provides powerful tools to inform about depression heterogeneity and molecular mechanisms related to clinical dimensions in MDD, which include a link to gut microbiome and lipids implicated in membrane structure and function.

Metabolite Profiling in Green Microalgae with Varying Degrees of Desiccation Tolerance

Trebouxiophyceae are microalgae occupying even extreme environments such as polar regions or deserts, terrestrial or aquatic, and can occur free-living or as lichen photobionts. Yet, it is poorly understood how environmental factors shape their metabolism. Here, we report on responses to light and temperature, and metabolic adjustments to desiccation in Diplosphaera epiphytica, isolated from a lichen, and Edaphochlorella mirabilis, isolated from Tundra soil, assessed via growth and photosynthetic performance parameters. Metabolite profiling was conducted by GC-MS. A meta-analysis together with data from a terrestrial and an aquatic Chlorella vulgaris strain reflected elements of phylogenetic relationship, lifestyle, and relative desiccation tolerance of the four algal strains. For example, compatible solutes associated with desiccation tolerance were up-accumulated in D. epiphytica, but also sugars and sugar alcohols typically produced by lichen photobionts. The aquatic C. vulgaris, the most desiccation-sensitive strain, showed the greatest variation in metabolite accumulation after desiccation and rehydration, whereas the most desiccation-tolerant strain, D. epiphytica, showed the least, suggesting that it has a more efficient constitutive protection from desiccation and/or that desiccation disturbed the metabolic steady-state less than in the other three strains. The authors hope that this study will stimulate more research into desiccation tolerance mechanisms in these under-investigated microorganisms.

Fraxinellone Induces Hepatotoxicity in Zebrafish through Oxidative Stress and the Transporters Pathway

Fraxinellone (FRA), a major active component from Cortex Dictamni, produces hepatotoxicity via the metabolization of furan rings by CYP450. However, the mechanism underlying the hepatotoxicity of FRA remains unclear. Therefore, zebrafish larvae at 72 h post fertilization were used to evaluate the metabolic hepatotoxicity of FRA and to explore the underlying molecular mechanisms. The results showed that FRA (10-30 μM) induced liver injury and obvious alterations in the metabolomics of zebrafish larvae. FRA induces apoptosis by increasing the level of ROS and activating the JNK/P53 pathway. In addition, FRA can induce cholestasis by down-regulating bile acid transporters P-gp, Bsep, and Ntcp. The addition of the CYP3A inhibitor ketoconazole (1 μM) significantly reduced the hepatotoxicity of FRA (30 μM), which indicated that FRA induced hepatotoxicity through CYP3A metabolism. Targeted metabolomics analysis indicates the changes in amino acid levels can be combined with molecular biology to clarify the mechanism of hepatotoxicity induced by FRA, and amino acid metabolism monitoring may provide a new method for the prevention and treatment of DILI from FRA.

Does oxygen affect ageing mechanisms of Pinus densiflora seeds? A matter of cytoplasmic physical state

During desiccation, the cytoplasm of orthodox seeds solidifies into an intracellular glass with highly restricted diffusion and molecular mobility. Temperature and water content govern seed ageing rates, while oxygen (O2) can promote deteriorative reactions. However, whether the cytoplasmic physical state affects involvement of O2 in seed ageing remains unresolved. We aged Pinus densiflora seeds by controlled deterioration (CD) at 45 °C and distinct relative humidity (RH), resulting in cells with a glassy (11% and 30% RH) or fluid (60% and 80% RH) cytoplasm. Hypoxic conditions (0.4% O2) during CD delayed seed deterioration, lipid peroxidation, and decline of antioxidants (glutathione, α-tocopherol, and γ-tocopherol), but only when the cytoplasm was glassy. In contrast, when the cytoplasm was fluid, seeds deteriorated at the same rate regardless of O2 availability, while being associated with limited lipid peroxidation, detoxification of lipid peroxide products, substantial loss of glutathione, and resumption of glutathione synthesis. Changes in metabolite profiles provided evidence of other O2-independent enzymatic reactions in a fluid cytoplasm, including aldo-keto reductase and glutamate decarboxylase activities. Biochemical profiles of seeds stored under seed bank conditions resembled those obtained after CD regimes that maintained a glassy cytoplasm. Overall, O2 contributed more to seed ageing when the cytoplasm was glassy, rather than fluid.

Multi-Fold Enhancement of Tocopherol Yields Employing High CO2 Supplementation and Nitrate Limitation in Native Isolate Monoraphidium sp

Tocopherols are the highly active form of the antioxidant molecules involved in scavenging of free radicals and protect the cell membranes from reactive oxygen species (ROS). In the present study, we focused on employing carbon supplementation with varying nitrate concentrations to enhance the total tocopherol yields in the native isolate Monoraphidium sp. CABeR41. The total tocopherol productivity of NRHC (Nitrate replete + 3% CO2) supplemented was (306.14 µg·L−1 d−1) which was nearly 2.5-fold higher compared to NRVLC (Nitrate replete + 0.03% CO2) (60.35 µg·L−1 d−1). The best tocopherol productivities were obtained in the NLHC (Nitrate limited + 3% CO2) supplemented cells (734.38 µg·L−1 d−1) accompanied by a significant increase in cell biomass (2.65-fold) and total lipids (6.25-fold). Further, global metabolomics using gas chromatography-mass spectrometry (GC-MS) was done in the defined conditions to elucidate the molecular mechanism during tocopherol accumulation. In the present study, the Monoraphidium sp. responded to nitrogen limitation by increase in nitrogen assimilation, with significant upregulation in gamma-Aminobutyric acid (GABA). Moreover, the tricarboxylic acid (TCA) cycle upregulation depicted increased availability of carbon skeletons and reducing power, which is leading to increased biomass yields along with the other biocommodities. In conclusion, our study depicts valorization of carbon dioxide as a cost-effective alternative for the enhancement of biomass along with tocopherols and other concomitant products like lipids and carotenoids in the indigenous strain Monoraphidium sp., as an industrial potential strain with relevance in nutraceuticals and pharmaceuticals.

Machine Learning-Based Retention Time Prediction of Trimethylsilyl Derivatives of Metabolites

In gas chromatography–mass spectrometry-based untargeted metabolomics, metabolites are identified by comparing mass spectra and chromatographic retention time with reference databases or standard materials. In that sense, machine learning has been used to predict the retention time of metabolites lacking reference data. However, the retention time prediction of trimethylsilyl derivatives of metabolites, typically analyzed in untargeted metabolomics using gas chromatography, has been poorly explored. Here, we provide a rationalized framework for machine learning-based retention time prediction of trimethylsilyl derivatives of metabolites in gas chromatography. We compared different machine learning paradigms, in addition to exploring the influence of the computational molecular structure representation to train the prediction models: fingerprint class and fingerprint calculation software. Our study challenged predicted retention time when using chemical ionization and electron impact ionization sources in simulated and real cases, demonstrating a good correct identity ranking capability by machine learning, despite observing a limited false identity filtering power in cases where a spectrum or a monoisotopic mass match to multiple candidates. Specifically, machine learning prediction yielded median absolute and relative retention index (relative retention time) errors of 37.1 retention index units and 2%, respectively. In addition, fingerprint class and fingerprint calculation software, as well as the molecular structural similarity between the training and test or real case sets, showed to be critical modulators of the prediction performance. Finally, we leveraged the structural similarity between the training and test or real case set to determine the probability that the prediction error is below a specific threshold. Overall, our study demonstrates that predicted retention time can provide insights into the true structure of unknown metabolites by ranking from the most to the least plausible molecular identity, and sets the guidelines to assess the confidence in metabolite identification using predicted retention time data.

Trypanosoma brucei: Metabolomics for analysis of cellular metabolism and drug discovery

BACKGROUND

Trypanosoma brucei is the causative agent of Human African Trypanosomiasis (also known as sleeping sickness), a disease causing serious neurological disorders and fatal if left untreated. Due to its lethal pathogenicity, a variety of treatments have been developed over the years, but which have some important limitations such as acute toxicity and parasite resistance. Metabolomics is an innovative tool used to better understand the parasite's cellular metabolism, and identify new potential targets, modes of action and resistance mechanisms. The metabolomic approach is mainly associated with robust analytical techniques, such as NMR and Mass Spectrometry. Applying these tools to the trypanosome parasite is, thus, useful for providing new insights into the sleeping sickness pathology and guidance towards innovative treatments.

AIM OF REVIEW

The present review aims to comprehensively describe the T. brucei biology and identify targets for new or commercialized antitrypanosomal drugs. Recent metabolomic applications to provide a deeper knowledge about the mechanisms of action of drugs or potential drugs against T. brucei are highlighted. Additionally, the advantages of metabolomics, alone or combined with other methods, are discussed.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Compared to other parasites, only few studies employing metabolomics have to date been reported on Trypanosoma brucei. Published metabolic studies, treatments and modes of action are discussed. The main interest is to evaluate the metabolomics contribution to the understanding of T. brucei's metabolism.

Integrated LC-MS and GC-MS-Based Metabolomics Reveal the Effects of Plant Competition on the Rye Metabolome

Plants compete with their neighbors about the limited resources available to them. Plants under induced stress resulting from competition may alter their metabolome to increase their resilience or enhance their defense mechanisms. In the present study, rye (Secale cereale) plants were cocultivated with different densities (3, 12, and 18 plants per pot) of Austrian pea (Pisum sativum subsp. arvense), hairy vetch (Vicia villosa), and Alexandrian clover (Trifolium alexandrinum L.) to elucidate the changes in the rye metabolome in response to the different levels of competition. Global metabolic profiling by liquid chromatography triple quadrupole tandem mass spectrometry (LC-QqQ-MS), liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF-MS), and gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) was performed on rye plants, and the acquired data were analyzed using uni- and multivariate statistics. Targeted analysis showed that a high level of competition reduced the concentration of aglycone benzoxazinoids (BXs) and increased glycoside BXs in rye roots. Untargeted metabolomics analysis indicated an increase in the rye root content of the allelopathic compounds 4-hydroxybenzoic acid and uracil in response to competition. Untargeted analysis of rye shoots revealed that the plant competition increased the d-pyroglutamic acid, which is an elicitor of reactive oxygen species (ROS). Our results have enhanced the knowledge of the biochemical response of plant species to cocultivation.

Comparative study for analysis of carbohydrates in biological samples

This work presents a comparative study for the analysis of carbohydrates for four common chromatographic methods, each coupled to mass spectrometry. Supercritical fluid chromatography (SFC), hydrophilic interaction liquid chromatography (HILIC), reversed-phase liquid chromatography (RP-LC) and gas chromatography (GC) with detection by triple quadrupole mass spectrometer (QqQ-MS) are compared. It is shown that gas chromatography and reversed-phase liquid chromatography, each after derivatisation, are superior to the other two methods in terms of separation performance. Furthermore, comparing the different working modes of the mass spectrometer, it can be determined that a targeted analysis, i.e. moving from full scan to single ion monitoring (SIM) and multiple reaction monitoring (MRM), results in an improvement in the sensitivity as well as the repeatability of the method, which has deficiencies especially in the analysis using HILIC. Overall, RP-LC-MS in MRM after derivatisation with 1-phenyl-3-methyl-5-pyrazolone (PMP) proved to be the most suitable method in terms of separation performance, sensitivity and repeatability for the analysis of monosaccharides. Detection limits in the nanomolar range were achieved, which corresponds to a mass concentration in the low µg/L range. The applicability of this method to different biological samples was investigated with various herbal liquors, pectins and a human glycoprotein.

Gas chromatography-mass spectrometry (GC-MS) profiling reveals substantial metabolome diversity in seabuckthorn (Hippophae rhamnoides L.) berries originating from different geographical regions in the Indian Himalayas

INTRODUCTION

Seabuckthorn (Hippophae rhamnoides L.) is a high-altitude plant with immense medicinal, nutritional, and therapeutic value. Earlier studies have documented the presence of various useful bioactive substances in this species; however, comprehensive metabolome profiling of seabuckthorn berries originating from different regions of the Indian Himalayas has not been undertaken.

OBJECTIVE

Metabolomic profiling of seabuckthorn berries originating from different geographical sites in the Himachal Pradesh and Jammu & Kashmir regions of the Indian Himalayas was performed by using gas chromatography-mass spectrometry.

MATERIALS AND METHODS

The GC-MS metabolome profiles of seabuckthorn berries collected from different sites (altitude 1,400-4,270 m; average temperature 8°C-27°C) were subjected to multivariate analysis following principal component analysis and hierarchical clustering analysis.

RESULTS

The GC-MS results showed substantial variability for berry metabolites, including fatty acids, alkyl ethers, and alkyl esters. Fatty acids and their esters were mainly responsible for the variation in the berry metabolome. The metabolite expression profile heat map revealed two distinct groups of seabuckthorn berries originating from Himachal Pradesh (Lahaul and Spiti) and Jammu & Kashmir (Leh, Nubra, and Kargil), the former showing higher expression of metabolites. Interestingly, a strong negative association existed between altitude and the amounts of metabolites such as amides, alkyl esters, alcohols, sugars, and sugar esters. In contrast, temperature showed a strong positive association with ketone and alkyl ether levels.

CONCLUSION

GC-MS profiling provides important phytochemical indicators to distinguish between seabuckthorn berries from different geographical sites. Our metabolome profiling analysis generated valuable information that will be useful in the formulation of various seabuckthorn products, benefiting farmers and industries.

Plasma Metabolite Profiles Following Consumption of Animal Protein and Soybean-Based Diet in Hypercholesterolemic Postmenopausal Women

Subjective reporting of food intake can be unreliable. No objective method is available to distinguish between diets differing in protein type. To address this gap, a secondary analysis of a randomized controlled cross-over feeding trial was conducted. Assessed were fasting plasma metabolite profiles and their associations with cardiometabolic risk factors (CMRFs). Hypercholesterolemic post-menopausal women (N = 11) were provided with diets containing predominantly animal protein (AP) and soy protein (SP). Untargeted metabolomics were used to determine the plasma metabolite profiles at the end of each diet phase. Concentrations of identified metabolites (N = 829) were compared using paired t-tests adjusted for false discovery rate, partial least square-discrimination analysis (PLS-DA) and receiver operating characteristics (ROC). Among the identified metabolites, 58 differed significantly between the AP and SP diets; the majority were phospholipids (n = 36), then amino acids (n = 10), xenobiotics (n = 7), vitamin/vitamin-related (n = 3) and lipids (n = 2). Of the top 10 metabolites, amino acid-derived metabolites, phospholipids and xenobiotics comprised the main categories differing due to dietary protein type. ROC curves confirmed that the top 10 metabolites were potential discriminating biomarkers for AP- and SP-rich diets. In conclusion, amino acid-derived metabolites, phosphatidylethanolamine-derived metabolites and isoflavones were identified as potential metabolite biomarkers distinguishing between dietary protein type.

A Potential Citrate Shunt in Erythrocytes of PKAN Patients Caused by Mutations in Pantothenate Kinase 2

Pantothenate kinase-associated neurodegeneration (PKAN) is a progressive neurodegenerative disease caused by mutations in the pantothenate kinase 2 (PANK2) gene and associated with iron deposition in basal ganglia. Pantothenate kinase isoforms catalyze the first step in coenzyme A (CoA) biosynthesis. Since PANK2 is the only isoform in erythrocytes, these cells are an excellent ex vivo model to study the effect of PANK2 point mutations on expression/stability and activity of the protein as well as on the downstream molecular consequences. PKAN erythrocytes containing the T528M PANK2 mutant had residual enzyme activities but variable PANK2 abundances indicating an impaired regulation of the protein. Patients with G521R/G521R, G521R/G262R, and R264N/L275fs PANK2 mutants had no residual enzyme activity and strongly reduced PANK2 abundance. G521R inactivates the catalytic activity of the enzyme, whereas G262R and the R264N point mutations impair the switch from the inactive to the active conformation of the PANK2 dimer. Metabolites in cytosolic extracts were analyzed by gas chromatography-mass spectrometry and multivariate analytic methods revealing changes in the carboxylate metabolism of erythrocytes from PKAN patients as compared to that of the carrier and healthy control. Assuming low/absent CoA levels in PKAN erythrocytes, changes are consistent with a model of altered citrate channeling where citrate is preferentially converted to α-ketoglutarate and α-hydroxyglutarate instead of being used for de novo acetyl-CoA generation. This finding hints at the importance of carboxylate metabolism in PKAN pathology with potential links to reduced cytoplasmic acetyl-CoA levels in neurons and to aberrant brain iron regulation.

Chemical Characterization and Non-targeted Analysis of Medical Device Extracts: A Review of Current Approaches, Gaps, and Emerging Practices

The developers of medical devices evaluate the biocompatibility of their device prior to FDA's review and subsequent introduction to the market. Chemical characterization, described in ISO 10993-18:2020, can generate information for toxicological risk assessment and is an alternative approach for addressing some biocompatibility end points (e.g., systemic toxicity, genotoxicity, carcinogenicity, reproductive/developmental toxicity) that can reduce the time and cost of testing and the need for animal testing. Additionally, chemical characterization can be used to determine whether modifications to the materials and manufacturing processes alter the chemistry of a patient-contacting device to an extent that could impact device safety. Extractables testing is one approach to chemical characterization that employs combinations of non-targeted analysis, non-targeted screening, and/or targeted analysis to establish the identities and quantities of the various chemical constituents that can be released from a device. Due to the difficulty in obtaining a priori information on all the constituents in finished devices, information generation strategies in the form of analytical chemistry testing are often used. Identified and quantified extractables are then assessed using toxicological risk assessment approaches to determine if reported quantities are sufficiently low to overcome the need for further chemical analysis, biological evaluation of select end points, or risk control. For extractables studies to be useful as a screening tool, comprehensive and reliable non-targeted methods are needed. Although non-targeted methods have been adopted by many laboratories, they are laboratory-specific and require expensive analytical instruments and advanced technical expertise to perform. In this Perspective, we describe the elements of extractables studies and provide an overview of the current practices, identified gaps, and emerging practices that may be adopted on a wider scale in the future. This Perspective is outlined according to the steps of an extractables study: information gathering, extraction, extract sample processing, system selection, qualification, quantification, and identification.

Pharmacometabonomic Association of Cyclophosphamide 4-hydroxylation in Hematopoietic Cell Transplant Recipients

The widely used alkylating agent cyclophosphamide (CY) has substantive interpatient variability in the area under the curve (AUC) of it and its metabolites. Numerous factors may influence the drug‐metabolizing enzymes that metabolize CY to 4‐hydroxycyclophosphamide (4HCY), the principal precursor to CY’s cytotoxic metabolite. We sought to identify endogenous metabolomics compounds (EMCs) associated with 4HCY formation clearance (ratio of 4HCY/CY AUC) using global metabolomics. Patients who undergo hematopoietic cell transplantation receiving post‐transplant CY (PT‐CY) were enrolled, cohort 1 (n = 26) and cohort 2 (n = 25) donating longitudinal blood samples before they started HCT (pre‐HCT), before infusion of the donor allograft (pre‐graft), before the first dose of PT‐CY (pre‐CY), and 24 h after the first dose of PT‐CY (24‐h post‐CY), which is also immediately before the second dose of CY. A total of 512 and 498 EMCs were quantitated in two cohorts, respectively. Both univariate linear regression with false discovery rate (FDR), and pathway enrichment analyses using a global association test were performed. At the pre‐CY time point, no EMCs were associated at FDR less than 0.1. At pre‐HCT, cohort 1 had one EMC (levoglucosan) survive the FDR threshold. At pre‐graft, cohort 1 and cohort 2 had 20 and 13 EMCs, respectively, exhibiting unadjusted p values less than 0.05, with the only EMCs having an FDR less than 0.1 being two unknown EMCs. At 24‐h post‐CY, there were three EMCs, two ketones, and threitol, at FDR less than 0.1 in cohort 2. These results demonstrate the potential of pharmacometabonomics, but future studies in larger samples are needed to optimize CY.

Comparative Evaluation of Plasma Metabolomic Data from Multiple Laboratories

In mass spectrometry-based metabolomics, the differences in the analytical results from different laboratories/machines are an issue to be considered because various types of machines are used in each laboratory. Moreover, the analytical methods are unique to each laboratory. It is important to understand the reality of inter-laboratory differences in metabolomics. Therefore, we have evaluated whether the differences in analytical methods, with the exception sample pretreatment and including metabolite extraction, are involved in the inter-laboratory differences or not. In this study, nine facilities are evaluated for inter-laboratory comparisons of metabolomic analysis. Identical dried samples prepared from human and mouse plasma are distributed to each laboratory, and the metabolites are measured without the pretreatment that is unique to each laboratory. In these measurements, hydrophilic and hydrophobic metabolites are analyzed using 11 and 7 analytical methods, respectively. The metabolomic data acquired at each laboratory are integrated, and the differences in the metabolomic data from the laboratories are evaluated. No substantial difference in the relative quantitative data (human/mouse) for a little less than 50% of the detected metabolites is observed, and the hydrophilic metabolites have fewer differences between the laboratories compared with hydrophobic metabolites. From evaluating selected quantitatively guaranteed metabolites, the proportion of metabolites without the inter-laboratory differences is observed to be slightly high. It is difficult to resolve the inter-laboratory differences in metabolomics because all laboratories cannot prepare the same analytical environments. However, the results from this study indicate that the inter-laboratory differences in metabolomic data are due to measurement and data analysis rather than sample preparation, which will facilitate the understanding of the problems in metabolomics studies involving multiple laboratories.

Challenges in Bioinformatics Workflows for Processing Microbiome Omics Data at Scale

The nascent field of microbiome science is transitioning from a descriptive approach of cataloging taxa and functions present in an environment to applying multi-omics methods to investigate microbiome dynamics and function. A large number of new tools and algorithms have been designed and used for very specific purposes on samples collected by individual investigators or groups. While these developments have been quite instructive, the ability to compare microbiome data generated by many groups of researchers is impeded by the lack of standardized application of bioinformatics methods. Additionally, there are few examples of broad bioinformatics workflows that can process metagenome, metatranscriptome, metaproteome and metabolomic data at scale, and no central hub that allows processing, or provides varied omics data that are findable, accessible, interoperable and reusable (FAIR). Here, we review some of the challenges that exist in analyzing omics data within the microbiome research sphere, and provide context on how the National Microbiome Data Collaborative has adopted a standardized and open access approach to address such challenges.

Evidence for Peroxisomal Dysfunction and Dysregulation of the CDP-Choline Pathway in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Background

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic and debilitating disease that is characterized by unexplained physical fatigue unrelieved by rest. Symptoms also include cognitive and sensory dysfunction, sleeping disturbances, orthostatic intolerance, and gastrointestinal problems. A syndrome clinically similar to ME/CFS has been reported following well-documented infections with the coronaviruses SARS-CoV and MERS-CoV. At least 10% of COVID-19 survivors develop post acute sequelae of SARS-CoV-2 infection (PASC). Although many individuals with PASC have evidence of structural organ damage, a subset have symptoms consistent with ME/CFS including fatigue, post exertional malaise, cognitive dysfunction, gastrointestinal disturbances, and postural orthostatic intolerance. These common features in ME/CFS and PASC suggest that insights into the pathogenesis of either may enrich our understanding of both syndromes, and could expedite the development of strategies for identifying those at risk and interventions that prevent or mitigate disease.

Methods

Using regression, Bayesian and enrichment analyses, we conducted targeted and untargeted metabolomic analysis of 888 metabolic analytes in plasma samples of 106 ME/CFS cases and 91 frequency-matched healthy controls.

Results

In ME/CFS cases, regression, Bayesian and enrichment analyses revealed evidence of peroxisomal dysfunction with decreased levels of plasmalogens. Other findings included decreased levels of several membrane lipids, including phosphatidylcholines and sphingomyelins, that may indicate dysregulation of the cytidine-5’-diphosphocholine pathway. Enrichment analyses revealed decreased levels of choline, ceramides and carnitines, and increased levels of long chain triglycerides (TG) and hydroxy-eicosapentaenoic acid. Elevated levels of dicarboxylic acids were consistent with abnormalities in the tricarboxylic acid cycle. Using machine learning algorithms with selected metabolites as predictors, we were able to differentiate female ME/CFS cases from female controls (highest AUC=0.794) and ME/CFS cases without self-reported irritable bowel syndrome (sr-IBS) from controls without sr-IBS (highest AUC=0.873).

Conclusion

Our findings are consistent with earlier ME/CFS work indicating compromised energy metabolism and redox imbalance, and highlight new abnormalities that may provide insights into the pathogenesis of ME/CFS.

Plasma levels of plasmalogens are decreased in patients with myalgic encephalomyelitis/chronic fatigue syndrome suggesting peroxisome dysfunction.

Comprehensive two-dimensional gas chromatography with mass spectrometry: an advanced bioanalytical technique for clinical metabolomics studies

This review highlights the current state of knowledge in the development of GC × GC-MS for the analysis of clinical metabolites. Selected applications are described as well as our perspectives on current challenges and potential future directions.

Oncogenic Gq/11 signaling acutely drives and chronically sustains metabolic reprogramming in uveal melanoma

Metabolic reprogramming has been shown to occur in uveal melanoma (UM), the most common intraocular tumor in adults. Mechanisms driving metabolic reprogramming in UM are poorly understood. Elucidation of these mechanisms could inform development of new therapeutic strategies for metastatic UM, which has poor prognosis because existing therapies are ineffective. Here, we determined whether metabolic reprogramming is driven by constitutively active mutant α-subunits of the heterotrimeric G proteins Gq or G11 (Gq/11), the oncogenic drivers in ∼90% of UM patients. Using PET-computed tomography imaging, microphysiometry, and GC/MS, we found that inhibition of oncogenic Gq/11 with the small molecule FR900359 (FR) attenuated glucose uptake by UM cells in vivo and in vitro, blunted glycolysis and mitochondrial respiration in UM cell lines and tumor cells isolated from patients, and reduced levels of several glycolytic and tricarboxylic acid cycle intermediates. FR acutely inhibited glycolysis and respiration and chronically attenuated expression of genes in both metabolic processes. UM therefore differs from other melanomas that exhibit a classic Warburg effect. Metabolic reprogramming in UM cell lines and patient samples involved protein kinase C and extracellular signal-regulated protein kinase 1/2 signaling downstream of oncogenic Gq/11. Chronic administration of FR upregulated expression of genes involved in metabolite scavenging and redox homeostasis, potentially as an adaptive mechanism explaining why FR does not efficiently kill UM tumor cells or regress UM tumor xenografts. These results establish that oncogenic Gq/11 signaling is a crucial driver of metabolic reprogramming in UM and lay a foundation for studies aimed at targeting metabolic reprogramming for therapeutic development.

Dietary Oxidized Linoleic Acids Modulate Fatty Acids in Mice

Objective

An elevated concentration of oxidized lipids along with the abnormal accumulation of lipids has been linked to the formation of atheromatous plaque and the development of cardiovascular diseases. This study aims to investigate if consumption of different concentrations of dietary oxidized linoleic acid alters the distribution of long chain fatty acids (LCFAs) within the liver relative to plasma in mice.

Methods

C57BL/6 male mice (n = 40) were divided into 4 groups: Standard chow as plain control (P group, n =10), Chow supplemented with linoleic acid 9 mg/mouse/day, linoleic control (C group, n=0), oxidized linoleic acid; 9 mg/mouse/day (A group, n=10) and oxidized linoleic acid 18 mg/mouse/day diet (B group, n=10). Liver and plasma samples were extracted, trans-esterified and subsequently analyzed using gas chromatography mass spectrometry (GC-MS) for LCFAs; palmitic acid, stearic acid, oleic acid, linoleic acid and arachidonic acid.

Results

LCFA methyl esters were eluted and identified based on their respective physiochemical characteristics of GCMS assay with inter assay coefficient of variation percentage (CV%, 1.81–5.28%), limits of quantification and limit of detection values (2.021–11.402 mg/mL and 1.016–4.430 mg/mL) respectively. Correlation analysis of liver and plasma lipids of the mice groups yielded coefficients (r=0.96, 0.6, 0.8 and 0.33) with fatty acid percentage total of (16%, 10%, 16% and 58%) for the P, C, A and B groups respectively.

Conclusion

The sustained consumption of a diet rich in oxidized linoleic acid disrupted fatty acid metabolism. The intake also resulted in elevated concentration of LCFAs that are precursors of bioactive metabolite molecule.

Inborn Errors of Metabolism Screening in Neonates: Current Perspective with Diagnosis and Therapy

Inborn errors of metabolism (IEMs) are rare hereditary or acquired disorders resulting from an enzymatic deformity in biochemical and metabolic pathways influencing proteins, fats, carbohydrate metabolism, or hampered some organelle function. Even though individual IEMs are uncommon, together, they represent a diverse class of genetic diseases, with new issues and disease mechanisms being portrayed consistently. IEM includes the extraordinary multifaceted nature of the fundamental pathophysiology, biochemical diagnosis, molecular level investigation, and complex therapeutic choices. However, due to the molecular, biochemical, and clinical heterogeneity of IEM, screening alone will not detect and diagnose all illnesses included in newborn screening programs. Early diagnosis prevents the emergence of severe clinical symptoms in the majority of IEM cases, lowering morbidity and death. The appearance of IEM disease can vary from neonates to adult people, with the more serious conditions showing up in juvenile stages along with significant morbidity as well as mortality. Advances in understanding the physiological, biochemical, and molecular etiologies of numerous IEMs by means of modalities, for instance, the latest molecular-genetic technologies, genome engineering knowledge, entire exome sequencing, and metabolomics, have prompted remarkable advancement in detection and treatment in modern times. In this review, we analyze the biochemical basis of IEMs, clinical manifestations, the present status of screening, ongoing advances, and efficiency of diagnosis in treatment for IEMs, along with prospects for further exploration as well as innovation.