High throughput transepithelial electrical resistance (TEER) measurements on perfused membrane-free epithelia.

Assessment of epithelial barrier function is critically important for studying healthy and diseased biological models. Here we introduce an instrument that measures transepithelial electrical resistance (TEER) of perfused epithelial tubes in the microfluidic OrganoPlate platform. The tubules are grown in microfluidic channels directly against an extracellular matrix, obviating the need for artificial filter membranes. We present TEER measurements on Caco-2 intestinal and renal proximal tubule epithelium. Forty tubules on one single plate were interrogated in less than a minute. We show that TEER measurement is significantly more sensitive than a fluorescent reporter leakage assay in response to staurosporine. We demonstrate a 40-channel time-lapse data acquisition over a 25 hour time period under flow conditions. We furthermore observed a 50% reduction in Caco-2 TEER values following exposure to a cocktail of inflammatory cytokines. To our best knowledge, this is the first instrument of its kind that allows routine TEER studies in perfused organ-on-a-chip systems without interference by artificial filter membranes. We believe the apparatus will contribute to accelerating routine adoption of perfused organ-on-a-chip systems in academic research and in industrial drug development.

The contribution of gut bacterial metabolites in the human immune signaling pathway of non-communicable diseases.

The interaction disorder between gut microbiota and its host has been documented in different non-communicable diseases (NCDs) such as metabolic syndrome, neurodegenerative disease, and autoimmune disease. The majority of these altered interactions arise through metabolic cross-talk between gut microbiota and host immune system, inducing a low-grade chronic inflammation that characterizes all NCDs. In this review, we discuss the contribution of bacterial metabolites to immune signaling pathways involved in NCDs. We then review recent advances that aid to rationally design microbial therapeutics. A deeper understanding of these intersections between host and gut microbiota metabolism using metabolomics-based system biology platform promises to reveal the fundamental mechanisms that drive metabolic predispositions to disease and suggest new avenues to use microbial therapeutic opportunities for NCDs treatment and prevention. Abbreviations: NCDs: non-communicable disease, IBD: inflammatory bowel disease, IL: interleukin, T2D: type 2 diabetes, SCFAs: short-chain fatty acids, HDAC: histone deacetylases, GPCR: G-protein coupled receptors, 5-HT: 5-hydroxytryptamine receptor signaling, DCs: dendritic cells, IECs: intestinal epithelial cells, T-reg: T regulatory cell, NF-κB: nuclear factor κB, TNF-α: tumor necrosis factor alpha, Th: T helper cell, CNS: central nervous system, ECs: enterochromaffin cells, NSAIDs: non-steroidal anti-inflammatory drugs, AhR: aryl hydrocarbon receptor, IDO: indoleamine 2,3-dioxygenase, QUIN: quinolinic acid, PC: phosphatidylcholine, TMA: trimethylamine, TMAO: trimethylamine N-oxide, CVD: cardiovascular disease, NASH: nonalcoholic steatohepatitis, BAs: bile acids, FXR: farnesoid X receptor, CDCA: chenodeoxycholic acid, DCA: deoxycholic acid, LCA: lithocholic acid, UDCA: ursodeoxycholic acid, CB: cannabinoid receptor, COBRA: constraint-based reconstruction and analysis.

Mechanism of action and potential applications of selective inhibition of microsomal prostaglandin E synthase-1-mediated PGE2 biosynthesis by sonlicromanol's metabolite KH176m.

Increased prostaglandin E2 (PGE2) levels were detected in mitochondrial disease patient cells harboring nuclear gene mutations in structural subunits of complex I, using a metabolomics screening approach. The increased levels of this principal inflammation mediator normalized following exposure of KH176m, an active redox-modulator metabolite of sonlicromanol (KH176). We next demonstrated that KH176m selectively inhibited lipopolysaccharide (LPS) or interleukin-1ß (IL-1ß)-induced PGE2 production in control skin fibroblasts. Comparable results were obtained in the mouse macrophage-like cell line RAW264.7. KH176m selectively inhibited mPGES-1 activity, as well as the inflammation-induced expression of mPGES-1. Finally, we showed that the effect of KH176m on mPGES-1 expression is due to the inhibition of a PGE2-driven positive feedback control-loop of mPGES-1 transcriptional regulation. Based on the results obtained we discuss potential new therapeutic applications of KH176m and its clinical stage parent drug candidate sonlicromanol in mitochondrial disease and beyond.

Publisher Correction: Menstrual cycle rhythmicity: metabolic patterns in healthy women.

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.

Perfused 3D angiogenic sprouting in a high-throughput in vitro platform.

Angiogenic sprouting, the growth of new blood vessels from pre-existing vessels, is orchestrated by cues from within the cellular microenvironment, such as biochemical gradients and perfusion. However, many of these cues are missing in current in vitro models of angiogenic sprouting. We here describe an in vitro platform that integrates both perfusion and the generation of stable biomolecular gradients and demonstrate its potential to study more physiologically relevant angiogenic sprouting and microvascular stabilization. The platform consists of an array of 40 individually addressable microfluidic units that enable the culture of perfused microvessels against a three-dimensional collagen-1 matrix. Upon the introduction of a gradient of pro-angiogenic factors, the endothelial cells differentiated into tip cells that invaded the matrix. Continuous exposure resulted in continuous migration and the formation of lumen by stalk cells. A combination of vascular endothelial growth factor-165 (VEGF-165), phorbol 12-myristate 13-acetate (PMA), and sphingosine-1-phosphate (S1P) was the most optimal cocktail to trigger robust, directional angiogenesis with S1P being crucial for guidance and repetitive sprout formation. Prolonged exposure forces the angiogenic sprouts to anastomose through the collagen to the other channel. This resulted in remodeling of the angiogenic sprouts within the collagen: angiogenic sprouts that anastomosed with the other perfusion channel remained stable, while those who did not retracted and degraded. Furthermore, perfusion with 150 kDa FITC-Dextran revealed that while the angiogenic sprouts were initially leaky, once they fully crossed the collagen lane they became leak tight. This demonstrates that once anastomosis occurred, the sprouts matured and suggests that perfusion can act as an important survival and stabilization factor for the angiogenic microvessels. The robustness of this platform in combination with the possibility to include a more physiological relevant three-dimensional microenvironment makes our platform uniquely suited to study angiogenesis in vitro.

Menstrual cycle rhythmicity: metabolic patterns in healthy women.

The menstrual cycle is an essential life rhythm governed by interacting levels of progesterone, estradiol, follicular stimulating, and luteinizing hormones. To study metabolic changes, biofluids were collected at four timepoints in the menstrual cycle from 34 healthy, premenopausal women. Serum hormones, urinary luteinizing hormone and self-reported menstrual cycle timing were used for a 5-phase cycle classification. Plasma and urine were analyzed using LC-MS and GC-MS for metabolomics and lipidomics; serum for clinical chemistries; and plasma for B vitamins using HPLC-FLD. Of 397 metabolites and micronutrients tested, 208 were significantly (p < 0.05) changed and 71 reached the FDR 0.20 threshold showing rhythmicity in neurotransmitter precursors, glutathione metabolism, the urea cycle, 4-pyridoxic acid, and 25-OH vitamin D. In total, 39 amino acids and derivatives and 18 lipid species decreased (FDR < 0.20) in the luteal phase, possibly indicative of an anabolic state during the progesterone peak and recovery during menstruation and the follicular phase. The reduced metabolite levels observed may represent a time of vulnerability to hormone related health issues such as PMS and PMDD, in the setting of a healthy, rhythmic state. These results provide a foundation for further research on cyclic differences in nutrient-related metabolites and may form the basis of novel nutrition strategies for women.

Bundling arrows: improving translational CNS drug development by integrated PK/PD-metabolomics.

INTRODUCTION: Diseases of the Central Nervous System (CNS) affect millions of people worldwide, with the number of people affected quickly growing. Unfortunately, the successful development of CNS-acting drugs is less than 10%, and this is attributed to the complexity of the CNS, unexpected side effects, difficulties in penetrating the blood-brain barrier and lack of biomarkers. Areas covered: Herein, the authors first review how pharmacokinetic/pharmacodynamic (PK/PD) models are designed to predict the dose-dependent time course of effect, and how they are used to translate drug effects from animal to man. Then, the authors discuss how pharmacometabolomics gives insight into system-wide pharmacological effects and why it is a promising method to study interspecies differences. Finally, the authors advocate the application of PK/PD-metabolomics modeling to advance translational CNS drug development by discussing its opportunities and challenges. Expert opinion: It is envisioned that PK/PD-metabolomics will increase our understanding of CNS drug effects and improve translational CNS drug development, thereby increasing success rates. The successful future development of this concept will require multi-level and longitudinal biomarker evaluation over a large dose range, multi-tissue biomarker evaluation, and the generation of a proof of principle by application to multiple CNS drugs in multiple species.

96 perfusable blood vessels to study vascular permeability in vitro.

Current in vitro models to test the barrier function of vasculature are based on flat, two-dimensional monolayers. These monolayers do not have the tubular morphology of vasculature found in vivo and lack important environmental cues from the cellular microenvironment, such as interaction with an extracellular matrix (ECM) and exposure to flow. To increase the physiological relevance of in vitro models of the vasculature, it is crucial to implement these cues and better mimic the native three-dimensional vascular architecture. We established a robust, high-throughput method to culture endothelial cells as 96 three-dimensional and perfusable microvessels and developed a quantitative, real-time permeability assay to assess their barrier function. Culture conditions were optimized for microvessel formation in 7 days and were viable for over 60 days. The microvessels exhibited a permeability to 20 kDa dextran but not to 150 kDa dextran, which mimics the functionality of vasculature in vivo. Also, a dose-dependent effect of VEGF, TNFα and several cytokines confirmed a physiologically relevant response. The throughput and robustness of this method and assay will allow end-users in vascular biology to make the transition from two-dimensional to three-dimensional culture methods to study vasculature.

Multivariate pharmacokinetic/pharmacodynamic (PKPD) analysis with metabolomics shows multiple effects of remoxipride in rats.

The study of central nervous system (CNS) pharmacology is limited by a lack of drug effect biomarkers. Pharmacometabolomics is a promising new tool to identify multiple molecular responses upon drug treatment. However, the pharmacodynamics is typically not evaluated in metabolomics studies, although being important properties of biomarkers. In this study we integrated pharmacometabolomics with pharmacokinetic/pharmacodynamic (PKPD) modeling to identify and quantify the multiple endogenous metabolite dose-response relations for the dopamine D2 antagonist remoxipride. Remoxipride (vehicle, 0.7 or 3.5mg/kg) was administered to rats. Endogenous metabolites were analyzed in plasma using a biogenic amine platform and PKPD models were derived for each single metabolite. These models were clustered on basis of proximity between their PKPD parameter estimates, and PKPD models were subsequently fitted for the individual clusters. Finally, the metabolites were evaluated for being significantly affected by remoxipride. In total 44 metabolites were detected in plasma, many of them showing a dose dependent decrease from baseline. We identified 6 different clusters with different time and dose dependent responses and 18 metabolites were revealed as potential biomarker. The glycine, serine and threonine pathway was associated with remoxipride pharmacology, as well as the brain uptake of the dopamine and serotonin precursors. This is the first time that pharmacometabolomics and PKPD modeling were integrated. The resulting PKPD cluster model described diverse pharmacometabolomics responses and provided a further understanding of remoxipride pharmacodynamics. Future research should focus on the simultaneous pharmacometabolomics analysis in brain and plasma to increase the interpretability of these responses.

Exome-sequencing in a large population-based study reveals a rare Asn396Ser variant in the LIPG gene associated with depressive symptoms.

Despite a substantial genetic component, efforts to identify common genetic variation underlying depression have largely been unsuccessful. In the current study we aimed to identify rare genetic variants that might have large effects on depression in the general population. Using high-coverage exome-sequencing, we studied the exonic variants in 1265 individuals from the Rotterdam study (RS), who were assessed for depressive symptoms. We identified a missense Asn396Ser mutation (rs77960347) in the endothelial lipase (LIPG) gene, occurring with an allele frequency of 1% in the general population, which was significantly associated with depressive symptoms (P-value=5.2 × 10-08, ß=7.2). Replication in three independent data sets (N=3612) confirmed the association of Asn396Ser (P-value=7.1 × 10-03, ß=2.55) with depressive symptoms. LIPG is predicted to have enzymatic function in steroid biosynthesis, cholesterol biosynthesis and thyroid hormone metabolic processes. The Asn396Ser variant is predicted to have a damaging effect on the function of LIPG. Within the discovery population, carriers also showed an increased burden of white matter lesions (P-value=3.3 × 10-02) and a higher risk of Alzheimer's disease (odds ratio=2.01; P-value=2.8 × 10-02) compared with the non-carriers. Together, these findings implicate the Asn396Ser variant of LIPG in the pathogenesis of depressive symptoms in the general population.

Quantifying Beta-Galactosylceramide Kinetics in Cerebrospinal Fluid of Healthy Subjects Using Deuterium Labeling.

Therapeutics promoting myelin synthesis may enhance recovery in demyelinating diseases, such as multiple sclerosis. However, no suitable method exists to quantify myelination. The turnover of galactosylceramide (myelin component) is indicative of myelination in mice, but its turnover has not been determined in humans. Here, six healthy subjects consumed 120 mL 70% D2 O daily for 70 days to label galactosylceramide. We then used mass spectrometry and compartmental modeling to quantify the turnover rate of galactosylceramide in cerebrospinal fluid. Maximum deuterium enrichment of body water ranged from 1.5-3.9%, whereas that of galactosylceramide was much lower: 0.05-0.14%. This suggests a slow turnover rate, which was confirmed by the model-estimated galactosylceramide turnover rate of 0.00168 day-1 , which corresponds to a half-life of 413 days. Additional studies in patients with multiple sclerosis are needed to investigate whether galactosylceramide turnover could be used as an outcome measure in clinical trials with remyelination therapies.

Mass spectrometry-based ligand binding assays on adenosine A1 and A2A receptors.

Conventional methods to measure ligand-receptor binding parameters typically require radiolabeled ligands as probes. Despite the robustness of radioligand binding assays, they carry inherent disadvantages in terms of safety precautions, expensive synthesis, special lab requirements, and waste disposal. Mass spectrometry (MS) is a method that can selectively detect ligands without the need of a label. The sensitivity of MS equipment increases progressively, and currently, it is possible to detect low ligand quantities that are usually found in ligand binding assays. We developed a label-free MS ligand binding (MS binding) assay on the adenosine A(1) and A(2A) receptors (A(1)AR and A(2A)AR), which are well-characterized members of the class A G protein-coupled receptor (GPCR) family. Radioligand binding assays for both receptors are well established, and ample data is available to compare and evaluate the performance of an MS binding assay. 1,3-Dipropyl-8-cyclopentyl-xanthine (DPCPX) and 4-(2-((7-amino-2-(furan-2-yl)-[1,2,4]triazolo[1,5-a]-[1,3,5]triazin-5-yl)amino)ethyl)phenol (ZM-241,385) are high-affinity ligands selective for the A(1)AR and A(2A)AR, respectively. To proof the feasibility of MS binding on the A(1)AR and A(2A)AR, we first developed an MS detection method for unlabeled DPCPX and ZM-241,385. To serve as internal standards, both compounds were also deuterium-labeled. Subsequently, we investigated whether the two unlabeled compounds could substitute for their radiolabeled counterparts as marker ligands in binding experiments, including saturation, displacement, dissociation, and competition association assays. Furthermore, we investigated the accuracy of these assays if the use of internal standards was excluded. The results demonstrate the feasibility of the MS binding assay, even in the absence of a deuterium-labeled internal standard, and provide great promise for the further development of label-free assays based on MS for other GPCRs.

Comprehensive metabolomics to evaluate the impact of industrial processing on the phytochemical composition of vegetable purees.

The effects of conventional industrial processing steps on global phytochemical composition of broccoli, tomato and carrot purees were investigated by using a range of complementary targeted and untargeted metabolomics approaches including LC-PDA for vitamins, (1)H NMR for polar metabolites, accurate mass LC-QTOF MS for semi-polar metabolites, LC-MRM for oxylipins, and headspace GC-MS for volatile compounds. An initial exploratory experiment indicated that the order of blending and thermal treatments had the highest impact on the phytochemicals in the purees. This blending-heating order effect was investigated in more depth by performing alternate blending-heating sequences in triplicate on the same batches of broccoli, tomato and carrot. For each vegetable and particularly in broccoli, a large proportion of the metabolites detected in the purees was significantly influenced by the blending-heating order, amongst which were potential health-related phytochemicals and flavour compounds like vitamins C and E, carotenoids, flavonoids, glucosinolates and oxylipins. Our metabolomics data indicates that during processing the activity of a series of endogenous plant enzymes, such as lipoxygenases, peroxidases and glycosidases, including myrosinase in broccoli, is key to the final metabolite composition and related quality of the purees.

Pharmacometabolomics reveals that serotonin is implicated in aspirin response variability.

While aspirin is generally effective for prevention of cardiovascular disease, considerable variation in drug response exists, resulting in some individuals displaying high on-treatment platelet reactivity. We used pharmacometabolomics to define pathways implicated in variation of response to treatment. We profiled serum samples from healthy subjects pre- and postaspirin (14 days, 81 mg/day) using mass spectrometry. We established a strong signature of aspirin exposure independent of response (15/34 metabolites changed). In our discovery (N = 80) and replication (N = 125) cohorts, higher serotonin levels pre- and postaspirin correlated with high, postaspirin, collagen-induced platelet aggregation. In a third cohort, platelets from subjects with the highest levels of serotonin preaspirin retained higher reactivity after incubation with aspirin than platelets from subjects with the lowest serotonin levels preaspirin (72 ± 8 vs. 61 ± 11%, P = 0.02, N = 20). Finally, ex vivo, serotonin strongly increased platelet reactivity after platelet incubation with aspirin (+20%, P = 4.9 × 10(-4), N = 12). These results suggest that serotonin is implicated in aspirin response variability.

Integrating metabolomics profiling measurements across multiple biobanks.

To optimize the quality of large scale mass-spectrometry based metabolomics data obtained from semiquantitative profiling measurements, it is important to use a strategy in which dedicated measurement designs are combined with a strict statistical quality control regime. This assures consistently high-quality results across measurements from individual studies, but semiquantitative data have been so far only comparable for samples measured within the same study. To enable comparability and integration of semiquantitative profiling data from different large scale studies over the time course of years, the measurement and quality control strategy has to be extended. We introduce a strategy to allow the integration of semiquantitative profiling data from different studies. We demonstrate that lipidomics data generated in samples from three different large biobanks acquired in the time course of 3 years can be effectively combined when using an appropriate measurement design and transfer model. This strategy paves the way toward an integrative usage of semiquantitative metabolomics data sets of multiple studies to validate biological findings in another study and/or to increase the statistical power for discovery of biomarkers or pathways by combining studies.

Purine pathway implicated in mechanism of resistance to aspirin therapy: pharmacometabolomics-informed pharmacogenomics.

Although aspirin is a well-established antiplatelet agent, the mechanisms of aspirin resistance remain poorly understood. Metabolomics allows for measurement of hundreds of small molecules in biological samples, enabling detailed mapping of pathways involved in drug response. We defined the metabolic signature of aspirin exposure in subjects from the Heredity and Phenotype Intervention Heart Study. Many metabolites, including known aspirin catabolites, changed on exposure to aspirin, and pathway enrichment analysis identified purine metabolism as significantly affected by drug exposure. Furthermore, purines were associated with aspirin response, and poor responders had higher postaspirin adenosine and inosine levels than did good responders (n = 76; both P < 4 × 10(-3)). Using our established "pharmacometabolomics-informed pharmacogenomics" approach, we identified genetic variants in adenosine kinase associated with aspirin response. Combining metabolomics and genomics allowed for more comprehensive interrogation of mechanisms of variation in aspirin response--an important step toward personalized treatment approaches for cardiovascular disease.

Discovery of early-stage biomarkers for diabetic kidney disease using ms-based metabolomics (FinnDiane study).

Diabetic kidney disease (DKD) is a devastating complication that affects an estimated third of patients with type 1 diabetes mellitus (DM). There is no cure once the disease is diagnosed, but early treatment at a sub-clinical stage can prevent or at least halt the progression. DKD is clinically diagnosed as abnormally high urinary albumin excretion rate (AER). We hypothesize that subtle changes in the urine metabolome precede the clinically significant rise in AER. To test this, 52 type 1 diabetic patients were recruited by the FinnDiane study that had normal AER (normoalbuminuric). After an average of 5.5 years of follow-up half of the subjects (26) progressed from normal AER to microalbuminuria or DKD (macroalbuminuria), the other half remained normoalbuminuric. The objective of this study is to discover urinary biomarkers that differentiate the progressive form of albuminuria from non-progressive form of albuminuria in humans. Metabolite profiles of baseline 24 h urine samples were obtained by gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) to detect potential early indicators of pathological changes. Multivariate logistic regression modeling of the metabolomics data resulted in a profile of metabolites that separated those patients that progressed from normoalbuminuric AER to microalbuminuric AER from those patients that maintained normoalbuminuric AER with an accuracy of 75% and a precision of 73%. As this data and samples are from an actual patient population and as such, gathered within a less controlled environment it is striking to see that within this profile a number of metabolites (identified as early indicators) have been associated with DKD already in literature, but also that new candidate biomarkers were found. The discriminating metabolites included acyl-carnitines, acyl-glycines and metabolites related to tryptophan metabolism. We found candidate biomarkers that were univariately significant different. This study demonstrates the potential of multivariate data analysis and metabolomics in the field of diabetic complications, and suggests several metabolic pathways relevant for further biological studies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0291-6) contains supplementary material, which is available to authorized users.

Modelling of migration from multi-layers and functional barriers: estimation of parameters.

Functional barriers form parts of multi-layer packaging materials, which are deemed to protect the food from migration of a broad range of contaminants, e.g. those associated with reused packaging. Often, neither the presence nor the identity of the contaminants is known, so that safety assessment of the materials has to rely on predictive tools. Several complementary freeware described here allow one to model diffusion in multi-layer films. These tools require the input of parameters that are not easy to determine or predict. Previous work has focused on the prediction of diffusion coefficients at storage temperatures of packaging in contact with food. However, many other kinetic and thermodynamic parameters are needed to describe transport properties during the processing of a material at high temperature and during its shelf-life. All parameters needed for the calculations are discussed. In order to propose default values, the approach consists of (1) reviewing the available literature data, (2) running experiments on polypropylene, polyethylene and poly(ethylene vinyl alcohol) in typical conditions (separately diffusion during processing and migration) and (3) simulating numerical sets for typical situations. Several freeware are proposed to simulate migration from multi-layers and functional barriers using the default parameters.