Trimethylamine N-oxide (TMAO) is a circulating microbiome-derived metabolite implicated in the development of atherosclerosis and cardiovascular disease (CVD). We investigated whether plasma levels... Show moreTrimethylamine N-oxide (TMAO) is a circulating microbiome-derived metabolite implicated in the development of atherosclerosis and cardiovascular disease (CVD). We investigated whether plasma levels of TMAO, its precursors (betaine, carnitine, deoxycarnitine, choline), and TMAO-to-precursor ratios are associated with clinical outcomes, including CVD and mortality. This was followed by an in-depth analysis of their genetic, gut microbial, and dietary determinants. The analyses were conducted in five Dutch prospective cohort studies including 7834 individuals. To further investigate association results, Mendelian Randomization (MR) was also explored. We found only plasma choline levels (hazard ratio [HR] 1.17, [95% CI 1.07; 1.28]) and not TMAO to be associated with CVD risk. Our association analyses uncovered 10 genome-wide significant loci, including novel genomic regions for betaine (6p21.1, 6q25.3), choline (2q34, 5q31.1), and deoxycarnitine (10q21.2, 11p14.2) comprising several metabolic gene associations, for example, CPS1 or PEMT. Furthermore, our analyses uncovered 68 gut microbiota associations, mainly related to TMAO-to-precursors ratios and the Ruminococcaceae family, and 16 associations of food groups and metabolites including fish-TMAO, meat-carnitine, and plant-based food-betaine associations. No significant association was identified by the MR approach. Our analyses provide novel insights into the TMAO pathway, its determinants, and pathophysiological impact on the general population. Show less
Singh, M.; Kiyuna, L.A.; Odendaal, C.; Bakker, B.M.; Harms, A.C.; Hankemeier, T. 2024
Monoacylglycerol lipase (MAGL) regulates endocannabinoid 2-arachidonoylglycerol (2-AG) and eicosanoid signalling. MAGL inhibition provides therapeutic opportunities but clinical potential is... Show moreMonoacylglycerol lipase (MAGL) regulates endocannabinoid 2-arachidonoylglycerol (2-AG) and eicosanoid signalling. MAGL inhibition provides therapeutic opportunities but clinical potential is limited by central nervous system (CNS)-mediated side effects. Here, we report the discovery of LEI-515, a peripherally restricted, reversible MAGL inhibitor, using high throughput screening and a medicinal chemistry programme. LEI-515 increased 2-AG levels in peripheral organs, but not mouse brain. LEI-515 attenuated liver necrosis, oxidative stress and inflammation in a CCl4-induced acute liver injury model. LEI-515 suppressed chemotherapy-induced neuropathic nociception in mice without inducing cardinal signs of CB1 activation. Antinociceptive efficacy of LEI-515 was blocked by CB2, but not CB1, antagonists. The CB1 antagonist rimonabant precipitated signs of physical dependence in mice treated chronically with a global MAGL inhibitor (JZL184), and an orthosteric cannabinoid agonist (WIN55,212-2), but not with LEI-515. Our data support targeting peripheral MAGL as a promising therapeutic strategy for developing safe and effective anti-inflammatory and analgesic agents. Show less
ContextThe endocannabinoid system (ECS) is a signaling system composed of endocannabinoids (eCBs), their receptors, and the enzymes involved in their synthesis and metabolism. Alterations in the... Show moreContextThe endocannabinoid system (ECS) is a signaling system composed of endocannabinoids (eCBs), their receptors, and the enzymes involved in their synthesis and metabolism. Alterations in the ECS are linked to the development of cardiometabolic diseases.ObjectiveHere, we investigated the relationship between plasma levels of eCBs and their analogues with body composition and cardiometabolic risk factors.MethodsThe study included 133 young adults (age 22.1 ± 2.2 years, 67% women). Fasting plasma levels of eCBs and their analogues were measured using liquid chromatography-tandem mass spectrometry. Body composition, brown adipose tissue (BAT) volume, glucose uptake, and traditional cardiometabolic risk factors were measured.ResultsPlasma levels of eCBs and several eCB analogues were positively correlated with adiposity and traditional cardiometabolic risk factors (eg, serum insulin and triacylglyceride levels, all r ≥ 0.17 and P ≤ .045). Plasma levels of 2-arachidonoyl glycerol and N-pentadecenoylethanolamine were negatively correlated with BAT volume and glucose uptake (all r ≤ −0.17 and P ≤ .047). We observed that the plasma levels of eCBs and their analogues were higher in metabolically unhealthy overweight–obese participants than in metabolically healthy overweight–obese participants.ConclusionOur findings show that the plasma levels of eCBs and their analogues are related to higher levels of adiposity and worse cardiometabolic profile. Show less
Singh, M.; Elfrink, H.L.; Harms, A.C.; Hankemeier, T. 2023
Single-cell heterogeneity in metabolism, drug resistance and disease type poses the need for analytical techniques for single-cell analysis. As the metabolome provides the closest view of the... Show moreSingle-cell heterogeneity in metabolism, drug resistance and disease type poses the need for analytical techniques for single-cell analysis. As the metabolome provides the closest view of the status quo in the cell, studying the metabolome at single-cell resolution may unravel said heterogeneity. A challenge in single-cell metabolome analysis is that metabolites cannot be amplified, so one needs to deal with picolitre volumes and a wide range of analyte concentrations. Due to high sensitivity and resolution, MS is preferred in single-cell metabolomics. Large numbers of cells need to be analysed for proper statistics; this requires high-throughput analysis, and hence automation of the analytical workflow. Significant advances in (micro)sampling methods, CE and ion mobility spectrometry have been made, some of which have been applied in high-throughput analyses. Microfluidics has enabled an automation of cell picking and metabolite extraction; image recognition has enabled automated cell identification. Many techniques have been used for data analysis, varying from conventional techniques to novel combinations of advanced chemometric approaches. Steps have been set in making data more findable, accessible, interoperable and reusable, but significant opportunities for improvement remain. Herein, advances in single-cell analysis workflows and data analysis are discussed, and recommendations are made based on the experimental goal. Show less
The evolving field of multi-omics combines data and provides methods for simultaneous analysis across several omics levels. Here, we integrated genomics (transmitted and non-transmitted polygenic... Show moreThe evolving field of multi-omics combines data and provides methods for simultaneous analysis across several omics levels. Here, we integrated genomics (transmitted and non-transmitted polygenic scores [PGSs]), epigenomics, and metabolomics data in a multi-omics framework to identify biomarkers for Attention-Deficit/Hyperactivity Disorder (ADHD) and investigated the connections among the three omics levels. We first trained single- and next multi-omics models to differentiate between cases and controls in 596 twins (cases = 14.8%) from the Netherlands Twin Register (NTR) demonstrating reasonable in-sample prediction through cross-validation. The multi-omics model selected 30 PGSs, 143 CpGs, and 90 metabolites. We confirmed previous associations of ADHD with glucocorticoid exposure and the transmembrane protein family TMEM, show that the DNA methylation of the MAD1L1 gene associated with ADHD has a relation with parental smoking behavior, and present novel findings including associations between indirect genetic effects and CpGs of the STAP2 gene. However, out-of-sample prediction in NTR participants (N = 258, cases = 14.3%) and in a clinical sample (N = 145, cases = 51%) did not perform well (range misclassification was [0.40, 0.57]). The results highlighted connections between omics levels, with the strongest connections between non-transmitted PGSs, CpGs, and amino acid levels and show that multi-omics designs considering interrelated omics levels can help unravel the complex biology underlying ADHD. Show less
BACKGROUND\nMETHOD\nRESULTS\nCONCLUSIONS\nMetabolic changes induced by the host immune response to pathogens found in patients with community-acquired pneumonia (CAP) may provide insight into its... Show moreBACKGROUND\nMETHOD\nRESULTS\nCONCLUSIONS\nMetabolic changes induced by the host immune response to pathogens found in patients with community-acquired pneumonia (CAP) may provide insight into its pathogenesis. In this study, we characterized differences in the host metabolic response to common CAP-associated pathogens.\nTargeted metabolomic profiling was performed on serum samples obtained from hospitalized CAP patients (n = 119) at admission. We quantified 347 unique metabolites across multiple biochemical classes, including amines, acylcarnitines, and signaling lipids. We evaluated if unique associations between metabolite levels and specific CAP-associated pathogens could be identified.\nSeveral acylcarnitines were found to be elevated in C. burnetii and herpes simplex virus and lowered in M. pneumoniae as compared to other pathogens. Phenylalanine and kynurenine were found elevated in L. pneumophila as compared to other pathogens. S-methylcysteine was elevated in patients with M. pneumoniae, and these patients also showed lowered cortisol levels in comparison to almost all other pathogens. For the herpes simplex virus, we observed a unique elevation of eicosanoids and several amines. Many lysophosphatidylcholines showed an altered profile in C. burnetii versus S. pneumoniae, L. pneumophila, and respiratory syncytial virus. Finally, phosphatidylcholines were negatively affected by the influenza virus in comparison to S. pneumoniae.\nIn this exploratory analysis, metabolites from different biochemical classes were found to be altered in serum samples from patients with different CAP-associated pathogens, which may be used for hypothesis generation in studies on differences in pathogen host response and pathogenesis of CAP. Show less
Single-cell metabolomics (SCMs) is a powerful tool for studying cellular heterogeneity by providing insight into the differences between individual cells. With the development of a set of promising... Show moreSingle-cell metabolomics (SCMs) is a powerful tool for studying cellular heterogeneity by providing insight into the differences between individual cells. With the development of a set of promising SCMs pipelines, this maturing technology is expected to be widely used in biomedical research. However, before SCMs is ready for primetime, there are some challenges to overcome. In this review, we summarize the trends and challenges in the development of SCMs. We also highlight the latest methodologies, applications, and sketch the perspective for integration with other omics and imaging approaches. Show less
Kallakkudi Pandian, K.; Matsui, M.; Hankemeier, T.; Ali, A.M.A.M.; Okubo-Kurihara, E. 2023
Single-cell metabolomics is a powerful tool that can reveal cellular heterogeneity and can elucidate the mechanisms of biological phenomena in detail. It is a promising approach in studying plants,... Show moreSingle-cell metabolomics is a powerful tool that can reveal cellular heterogeneity and can elucidate the mechanisms of biological phenomena in detail. It is a promising approach in studying plants, especially when cellular heterogeneity has an impact on different biological processes. In addition, metabolomics, which can be regarded as a detailed phenotypic analysis, is expected to answer previously unrequited questions which will lead to expansion of crop production, increased understanding of resistance to diseases, and in other applications as well. In this review, we will introduce the flow of sample acquisition and single-cell techniques to facilitate the adoption of single-cell metabolomics. Furthermore, the applications of single-cell metabolomics will be summarized and reviewed. Show less
