Rationale: Hypertrophied hearts switch from mainly using fatty acids (FAs) to an increased reliance on glucose for energy production. It has been shown that preserving FA oxidation (FAO) prevents the pathological shift of substrate preference, preserves cardiac function and energetics, and reduces cardiomyocyte hypertrophy during cardiac stresses. However, it remains elusive whether substrate metabolism regulates cardiomyocyte hypertrophy directly or via a secondary effect of improving cardiac energetics. Objective: The goal of this study was to determine the mechanisms of how preservation of FAO prevents the hypertrophic growth of cardiomyocytes. Methods and Results: We cultured adult rat cardiomyocytes in a medium containing glucose and mixed-chain FAs and induced pathological hypertrophy by phenylephrine. Phenylephrine-induced hypertrophy was associated with increased glucose consumption and higher intracellular aspartate levels, resulting in increased synthesis of nucleotides, RNA, and proteins. These changes could be prevented by increasing FAO via deletion of ACC2 (acetyl-CoA-carboxylase 2) in phenylephrine-stimulated cardiomyocytes and in pressure overload–induced cardiac hypertrophy in vivo. Furthermore, aspartate supplementation was sufficient to reverse the antihypertrophic effect of ACC2 deletion demonstrating a causal role of elevated aspartate level in cardiomyocyte hypertrophy. 15N and 13C stable isotope tracing revealed that glucose but not glutamine contributed to increased biosynthesis of aspartate, which supplied nitrogen for nucleotide synthesis during cardiomyocyte hypertrophy. Conclusions: Our data show that increased glucose consumption is required to support aspartate synthesis that drives the increase of biomass during cardiac hypertrophy. Preservation of FAO prevents the shift of metabolic flux into the anabolic pathway and maintains catabolic metabolism for energy production, thus preventing cardiac hypertrophy and improving myocardial energetics.

Rationale: Lipid overload-induced heart dysfunction is characterized by cardiomyocyte death, myocardial remodeling, and compromised contractility, but the impact of excessive lipid supply on cardiac function remains poorly understood. Objective: To investigate the regulation and function of the mitochondrial fission protein Drp1 (dynamin-related protein 1) in lipid overload-induced cardiomyocyte death and heart dysfunction. Methods and Results: Mice fed a high-fat diet (HFD) developed signs of obesity and type II diabetes mellitus, including hyperlipidemia, hyperglycemia, hyperinsulinemia, and hypertension. HFD for 18 weeks also induced heart hypertrophy, fibrosis, myocardial insulin resistance, and cardiomyocyte death. HFD stimulated mitochondrial fission in mouse hearts. Furthermore, HFD increased the protein level, phosphorylation (at the activating serine 616 sites), oligomerization, mitochondrial translocation, and GTPase activity of Drp1 in mouse hearts, indicating that Drp1 was activated. Monkeys fed a diet high in fat and cholesterol for 2.5 years also exhibited myocardial damage and Drp1 activation in the heart. Interestingly, HFD decreased nicotinamide adenine dinucleotide (oxidized) levels and increased Drp1 acetylation in the heart. In adult cardiomyocytes, palmitate increased Drp1 acetylation, phosphorylation, and protein levels, and these increases were abolished by restoration of the decreased nicotinamide adenine dinucleotide (oxidized) level. Proteomics analysis and in vitro screening revealed that Drp1 acetylation at lysine 642 (K642) was increased by HFD in mouse hearts and by palmitate incubation in cardiomyocytes. The nonacetylated Drp1 mutation (K642R) attenuated palmitate-induced Drp1 activation, its interaction with voltage-dependent anion channel 1, mitochondrial fission, contractile dysfunction, and cardiomyocyte death. Conclusions: These findings uncover a novel mechanism that contributes to lipid overload-induced heart hypertrophy and dysfunction. Excessive lipid supply created an intracellular environment that facilitated Drp1 acetylation, which, in turn, increased its activity and mitochondrial translocation, resulting in cardiomyocyte dysfunction and death. Thus, Drp1 may be a critical mediator of lipid overload-induced heart dysfunction as well as a potential target for therapy.

Modern biomarker and translational research as well as personalized health care studies rely heavily on powerful omics’ technologies, including metabolomics and lipidomics. However, to translate metabolomics and lipidomics discoveries into a high-throughput clinical setting, standardization is of utmost importance. Here, we compared and benchmarked a quantitative lipidomics platform. The employed Lipidyzer platform is based on lipid class separation by means of differential mobility spectrometry with subsequent multiple reaction monitoring. Quantitation is achieved by the use of 54 deuterated internal standards and an automated informatics approach. We investigated the platform performance across nine laboratories using NIST SRM 1950–Metabolites in Frozen Human Plasma, and three NIST Candidate Reference Materials 8231–Frozen Human Plasma Suite for Metabolomics (high triglyceride, diabetic, and African-American plasma). In addition, we comparatively analyzed 59 plasma samples from individuals with familial hypercholesterolemia from a clinical cohort study. We provide evidence that the more practical methyl-tert-butyl ether extraction outperforms the classic Bligh and Dyer approach and compare our results with two previously published ring trials. In summary, we present standardized lipidomics protocols, allowing for the highly reproducible analysis of several hundred human plasma lipids, and present detailed molecular information for potentially disease relevant and ethnicity-related materials.

Differential mobility spectrometry (DMS) is highly useful for shotgun lipidomic analysis because it overcomes difficulties in measuring isobaric species within a complex lipid sample and allows for acyl tail characterization of phospholipid species. Despite these advantages, the resulting workflow presents technical challenges, including the need to tune the DMS before every batch to update compensative voltages settings within the method. The Sciex Lipidyzer platform uses a Sciex 5500 QTRAP with a DMS (SelexION), an LC system configured for direction infusion experiments, an extensive set of standards designed for quantitative lipidomics, and a software package (Lipidyzer Workflow Manager) that facilitates the workflow and rapidly analyzes the data. Although the Lipidyzer platform remains very useful for DMS-based shotgun lipidomics, the software is no longer updated for current versions of Analyst and Windows. Furthermore, the software is fixed to a single workflow and cannot take advantage of new lipidomics standards or analyze additional lipid species. To address this multitude of issues, we developed Shotgun Lipidomics Assistant (SLA), a Python-based application that facilitates DMS-based lipidomics workflows. SLA provides the user with flexibility in adding and subtracting lipid and standard MRMs. It can report quantitative lipidomics results from raw data in minutes, comparable to the Lipidyzer software. We show that SLA facilitates an expanded lipidomics analysis that measures over 1450 lipid species across 17 (sub)­classes. Lastly, we demonstrate that the SLA performs isotope correction, a feature that was absent from the original software.

Broad-based, targeted metabolite profiling using mass spectrometry (MS) has become a major platform used in the field of metabolomics for a variety of applications. However, quantitative MS analysis is challenging owing to numerous factors including (1) the need for, ideally, isotope-labeled internal standards for each metabolite, (2) the fact that such standards may be unavailable or prohibitively costly, (3) the need to maintain the standards’ concentrations close to those of the target metabolites, and (4) the alternative use of time-consuming calibration curves for each target metabolite. Here, we introduce a new method in which metabolites from a single serum specimen are quantified on the basis of a recently developed NMR method [Nagana Gowda et al. Anal. Chem. 2015, 87, 706] and then used as references for absolute metabolite quantitation using MS. The MS concentrations of 30 metabolites thus derived for test serum samples exhibited excellent correlations with the NMR ones (R2 > 0.99) with a median CV of 3.2%. This NMR-guided-MS quantitation approach is simple and easy to implement and offers new avenues for the routine quantification of blood metabolites using MS. The demonstration that NMR and MS data can be compared and correlated when using identical sample preparations allows improved opportunities to exploit their combined strengths for biomarker discovery and unknown-metabolite identification. Intriguingly, however, metabolites including glutamine, pyroglutamic acid, glucose, and sarcosine correlated poorly with NMR data because of stability issues in their MS analyses or weak or overlapping signals. Such information is potentially important for improving biomarker discovery and biological interpretations. Further, the new quantitation method demonstrated here for human blood serum can in principle be extended to a variety of biological mixtures.