John K. Meissen

LipidBlast in silico tandem mass spectrometry database for lipid identification

Current tandem mass spectral libraries for lipid annotations in metabolomics are limited in size and diversity. We provide a freely available computer-generated tandem mass spectral library of 212,516 spectra covering 119,200 compounds from 26 lipid compound classes, including phospholipids, glycerolipids, bacterial lipoglycans and plant glycolipids. We show platform independence by using tandem mass spectra from 40 different mass spectrometer types including low-resolution and high-resolution instruments.

Qualitative analysis of algal secretions with multiple mass spectrometric platforms

Lipid secretions from algae pose a great opportunity for engineering biofueler feedstocks. The lipid exudates could be interesting from a process engineering perspective because lipids could be collected directly from the medium without harvesting and disrupting cells. We here report on the extracellular secretions of algal metabolites from the strain UTEX 2341 (Chlorella minutissima) into the culture medium. No detailed analysis of these lipid secretions has been performed to date. Using multiple mass spectrometric platforms, we observed around 1000 compounds and were able to annotate 50 lipids by means of liquid chromatography coupled to accurate mass quadrupole time-of-flight mass spectrometry (LC-QTOF), direct infusion with positive and negative electrospray ion trap mass spectrometry and gas chromatography coupled to mass spectrometry (GC-MS). These compounds were annotated by tandem mass spectral (MS/MS) database matching and retention time range filtering. We observed a series of triacylglycerols (TG), sulfoquinovosyldiacylglycerols (SQDG), phosphatidylinositols and phosphatidylglycerols, as well as betaine lipids diacylglyceryl-N,N,N-trimethylhomoserines (DGTS).

Induced Pluripotent Stem Cells Show Metabolomic Differences to Embryonic Stem Cells in Polyunsaturated Phosphatidylcholines and Primary Metabolism

Induced pluripotent stem cells are different from embryonic stem cells as shown by epigenetic and genomics analyses. Depending on cell types and culture conditions, such genetic alterations can lead to different metabolic phenotypes which may impact replication rates, membrane properties and cell differentiation. We here applied a comprehensive metabolomics strategy incorporating nanoelectrospray ion trap mass spectrometry (MS), gas chromatography-time of flight MS, and hydrophilic interaction- and reversed phase-liquid chromatography-quadrupole time-of-flight MS to examine the metabolome of induced pluripotent stem cells (iPSCs) compared to parental fibroblasts as well as to reference embryonic stem cells (ESCs). With over 250 identified metabolites and a range of structurally unknown compounds, quantitative and statistical metabolome data were mapped onto a metabolite networks describing the metabolic state of iPSCs relative to other cell types. Overall iPSCs exhibited a striking shift metabolically away from parental fibroblasts and toward ESCs, suggestive of near complete metabolic reprogramming. Differences between pluripotent cell types were not observed in carbohydrate or hydroxyl acid metabolism, pentose phosphate pathway metabolites, or free fatty acids. However, significant differences between iPSCs and ESCs were evident in phosphatidylcholine and phosphatidylethanolamine lipid structures, essential and non-essential amino acids, and metabolites involved in polyamine biosynthesis. Together our findings demonstrate that during cellular reprogramming, the metabolome of fibroblasts is also reprogrammed to take on an ESC-like profile, but there are select unique differences apparent in iPSCs. The identified metabolomics signatures of iPSCs and ESCs may have important implications for functional regulation of maintenance and induction of pluripotency.

Improved Metabolic Health Alters Host Metabolism in Parallel with Changes in Systemic Xeno-Metabolites of Gut Origin

Novel plasma metabolite patterns reflective of improved metabolic health (insulin sensitivity, fitness, reduced body weight) were identified before and after a 14–17 wk weight loss and exercise intervention in sedentary, obese insulin-resistant women. To control for potential confounding effects of diet- or microbiome-derived molecules on the systemic metabolome, sampling was during a tightly-controlled feeding test week paradigm. Pairwise and multivariate analysis revealed intervention- and insulin-sensitivity associated: (1) Changes in plasma xeno-metabolites (“non-self” metabolites of dietary or gut microbial origin) following an oral glucose tolerance test (e.g. higher post-OGTT propane-1,2,3-tricarboxylate [tricarballylic acid]) or in the overnight-fasted state (e.g., lower γ-tocopherol); (2) Increased indices of saturated very long chain fatty acid elongation capacity; (3) Increased post-OGTT α-ketoglutaric acid (α-KG), fasting α-KG inversely correlated with Matsuda index, and altered patterns of malate, pyruvate and glutamine hypothesized to stem from improved mitochondrial efficiency and more robust oxidation of glucose. The results support a working model in which improved metabolic health modifies host metabolism in parallel with altering systemic exposure to xeno-metabolites. This highlights that interpretations regarding the origins of peripheral blood or urinary “signatures” of insulin resistance and metabolic health must consider the potentially important contribution of gut-derived metabolites toward the hosts metabolome.

Muscle uncoupling protein 3 overexpression mimics endurance training and reduces circulating biomarkers of incomplete β-oxidation

Exercise substantially improves metabolic health, making the elicited mechanisms important targets for novel therapeutic strategies. Uncoupling protein 3 (UCP3) is a mitochondrial inner membrane protein highly selectively expressed in skeletal muscle. Here we report that moderate UCP3 overexpression (roughly 3‐fold) in muscles of UCP3 transgenic (UCP3Tg) mice acts as an exercise mimetic in many ways. UCP3 overexpression increased spontaneous activity (~40%) and energy expenditure (~5–10%) and decreased oxidative stress (~ 15–20%), similar to exercise training in wild‐type (WT) mice. The increase in complete fatty acid oxidation (FAO; ~30% for WT and ~70% for UCP3 Tg) and energy expenditure (~8% for WT and 15% for UCP3 Tg) in response to endurance training was higher in UCP3 Tg than in WT mice, showing an additive effect of UCP3 and endurance training on these two parameters. Moreover, increases in circulating short‐chain acylcarnitines in response to acute exercise in untrained WT mice were absent with training or in UCP3 Tg mice. UCP3 overexpression had the same effect as training in decreasing long‐chain acylcarnitines. Outcomes coincided with a reduction in muscle carnitine acetyltransferase activity that catalyzes the formation of acylcarnitines. Overall, results are consistent with the conclusions that circulating acylcarnitines could be used as a marker of incomplete muscle FAO and that UCP3 is a potential target for the treatment of prevalent metabolic diseases in which muscle FAO is affected.—Aguer, C., Fiehn, O., Seifert, E. L., Bézaire, V., Meissen, J. K., Daniels, A., Scott, K., Renaud, J.‐M., Padilla, M., Bickel, D. R., Dysart, M., Adams, S. H., Harper, M.‐E. Muscle uncoupling protein 3 overexpression mimics endurance training and reduces circulating biomarkers of incomplete β‐oxidation. FASEB J. 27, 4213–4225 (2013). www.fasebj.org

Comparative Effects of Fructose and Glucose on Lipogenic Gene Expression and Intermediary Metabolism in HepG2 Liver Cells

Consumption of large amounts of fructose or sucrose increases lipogenesis and circulating triglycerides in humans. Although the underlying molecular mechanisms responsible for this effect are not completely understood, it is possible that as reported for rodents, high fructose exposure increases expression of the lipogenic enzymes fatty acid synthase (FAS) and acetyl-CoA carboxylase (ACC-1) in human liver. Since activation of the hexosamine biosynthesis pathway (HBP) is associated with increases in the expression of FAS and ACC-1, it raises the possibility that HBP-related metabolites would contribute to any increase in hepatic expression of these enzymes following fructose exposure. Thus, we compared lipogenic gene expression in human-derived HepG2 cells after incubation in culture medium containing glucose alone or glucose plus 5 mM fructose, using the HBP precursor 10 mM glucosamine (GlcN) as a positive control. Cellular metabolite profiling was conducted to analyze differences between glucose and fructose metabolism. Despite evidence for the active uptake and metabolism of fructose by HepG2 cells, expression of FAS or ACC-1 did not increase in these cells compared with those incubated with glucose alone. Levels of UDP-N-acetylglucosamine (UDP-GlcNAc), the end-product of the HBP, did not differ significantly between the glucose and fructose conditions. Exposure to 10 mM GlcN for 10 minutes to 24 hours resulted in 8-fold elevated levels of intracellular UDP-GlcNAc (P<0.001), as well as a 74–126% increase in FAS (P<0.05) and 49–95% increase in ACC-1 (P<0.01) expression above controls. It is concluded that in HepG2 liver cells cultured under standard conditions, sustained exposure to fructose does not result in an activation of the HBP or increased lipogenic gene expression. Should this scenario manifest in human liver in vivo, it would suggest that high fructose consumption promotes triglyceride synthesis primarily through its action to provide lipid precursor carbon and not by activating lipogenic gene expression.

Plants utilize a highly conserved system for repair of NADH and NADPH hydrates

The hydrates formed from NADH and NADPH by chemical or enzymatic damage are repaired in plants by highly conserved enzymes that are targeted to multiple compartments. NADH and NADPH undergo spontaneous and enzymatic reactions that produce R and S forms of NAD(P)H hydrates [NAD(P)HX], which are not electron donors and inhibit various dehydrogenases. In bacteria, yeast (Saccharomyces cerevisiae), and mammals, these hydrates are repaired by the tandem action of an ADP- or ATP-dependent dehydratase that converts (S)-NAD(P)HX to NAD(P)H and an epimerase that facilitates interconversion of the R and S forms. Plants have homologs of both enzymes, the epimerase homolog being fused to the vitamin B6 salvage enzyme pyridoxine 5′-phosphate oxidase. Recombinant maize (Zea mays) and Arabidopsis (Arabidopsis thaliana) NAD(P)HX dehydratases (GRMZM5G840928, At5g19150) were able to reconvert (S)-NAD(P)HX to NAD(P)H in an ATP-dependent manner. Recombinant maize and Arabidopsis epimerases (GRMZM2G061988, At5g49970) rapidly interconverted (R)- and (S)-NAD(P)HX, as did a truncated form of the Arabidopsis epimerase lacking the pyridoxine 5′-phosphate oxidase domain. All plant NAD(P)HX dehydratase and epimerase sequences examined had predicted organellar targeting peptides with a potential second start codon whose use would eliminate the targeting peptide. In vitro transcription/translation assays confirmed that both start sites were used. Dual import assays with purified pea (Pisum sativum) chloroplasts and mitochondria, and subcellular localization of GFP fusion constructs in tobacco (Nicotiana tabacum) suspension cells, indicated mitochondrial, plastidial, and cytosolic localization of the Arabidopsis epimerase and dehydratase. Ablation of the Arabidopsis dehydratase gene raised seedling levels of all NADHX forms by 20- to 40-fold, and levels of one NADPHX form by 10- to 30-fold. We conclude that plants have a canonical two-enzyme NAD(P)HX repair system that is directed to three subcellular compartments via the use of alternative translation start sites.

Identifying metabolites by integrating metabolome databases with mass spectrometry cheminformatics

Novel metabolites distinct from canonical pathways can be identified through the integration of three cheminformatics tools: BinVestigate, which queries the BinBase gas chromatography–mass spectrometry (GC-MS) metabolome database to match unknowns with biological metadata across over 110,000 samples; MS-DIAL 2.0, a software tool for chromatographic deconvolution of high-resolution GC-MS or liquid chromatography–mass spectrometry (LC-MS); and MS-FINDER 2.0, a structure-elucidation program that uses a combination of 14 metabolome databases in addition to an enzyme promiscuity library. We showcase our workflow by annotating N-methyl-uridine monophosphate (UMP), lysomonogalactosyl-monopalmitin, N-methylalanine, and two propofol derivatives.

The Iceman’s Last Meal Consisted of Fat, Wild Meat, and Cereals

Summary The history of humankind is marked by the constant adoption of new dietary habits affecting human physiology, metabolism, and even the development of nutrition-related disorders. Despite clear archaeological evidence for the shift from hunter-gatherer lifestyle to agriculture in Neolithic Europe [1], very little information exists on the daily dietary habits of our ancestors. By undertaking a complementary -omics approach combined with microscopy, we analyzed the stomach content of the Iceman, a 5,300-year-old European glacier mummy [2, 3]. He seems to have had a remarkably high proportion of fat in his diet, supplemented with fresh or dried wild meat, cereals, and traces of toxic bracken. Our multipronged approach provides unprecedented analytical depth, deciphering the nutritional habit, meal composition, and food-processing methods of this Copper Age individual.

Erratum: Muscle uncoupling protein 3 overexpression mimics endurance training and reduces circulating biomarkers of incomplete β-oxidation (FASEB Journal (2013) 27 (4213- 4225) DOI: 10.1096/fj.13-234302)

Regarding the article: “Muscle uncoupling protein 3 overexpression mimics endurance training and reduces circulating biomarkers of incomplete -oxidation,” by Céline Aguer, Oliver Fiehn, Erin L. Seifert, Véronic Bézaire, John K. Meissen, Amanda Daniels, Kyle Scott, Jean-Marc Renaud, Marta Padilla, David R. Bickel, Michael Dysart, Sean H. Adams, and Mary-Ellen Harper, published in FASEB J. October 2013 27:4213– 4225; doi: 10.1096/fj.13-234302. In Figure 3, Panel E, the units labeled in the y-axis are incorrect: “kcal/min/g” should read “kcal/h/kg.”