Sean C. Sapcariu

Immunoresponsive Gene 1 and Itaconate Inhibit Succinate Dehydrogenase to Modulate Intracellular Succinate Levels

Metabolic reprogramming is emerging as a hallmark of the innate immune response, and the dynamic control of metabolites such as succinate serves to facilitate the execution of inflammatory responses in macrophages and other immune cells. Immunoresponsive gene 1 (Irg1) expression is induced by inflammatory stimuli, and its enzyme product cis-aconitate decarboxylase catalyzes the production of itaconate from the tricarboxylic acid cycle. Here we identify an immunometabolic regulatory pathway that links Irg1 and itaconate production to the succinate accumulation that occurs in the context of innate immune responses. Itaconate levels and Irg1 expression correlate strongly with succinate during LPS exposure in macrophages and non-immune cells. We demonstrate that itaconate acts as an endogenous succinate dehydrogenase inhibitor to cause succinate accumulation. Loss of itaconate production in activated macrophages from Irg1−/− mice decreases the accumulation of succinate in response to LPS exposure. This metabolic network links the innate immune response and tricarboxylic acid metabolism to function of the electron transport chain.

Pro-inflammatory Macrophages Sustain Pyruvate Oxidation through Pyruvate Dehydrogenase for the Synthesis of Itaconate and to Enable Cytokine Expression

Upon stimulation with Th1 cytokines or bacterial lipopolysaccharides, resting macrophages shift their phenotype toward a pro-inflammatory state as part of the innate immune response. LPS-activated macrophages undergo profound metabolic changes to adapt to these new physiological requirements. One key step to mediate this metabolic adaptation is the stabilization of HIF1α, which leads to increased glycolysis and lactate release, as well as decreased oxygen consumption. HIF1 abundance can result in the induction of the gene encoding pyruvate dehydrogenase kinase 1 (PDK1), which inhibits pyruvate dehydrogenase (PDH) via phosphorylation. Therefore, it has been speculated that pyruvate oxidation through PDH is decreased in pro-inflammatory macrophages. However, to answer this open question, an in-depth analysis of this metabolic branching point was so far lacking. In this work, we applied stable isotope-assisted metabolomics techniques and demonstrate that pyruvate oxidation is maintained in mature pro-inflammatory macrophages. Glucose-derived pyruvate is oxidized via PDH to generate citrate in the mitochondria. Citrate is used for the synthesis of the antimicrobial metabolite itaconate and for lipogenesis. An increased demand for these metabolites decreases citrate oxidation through the tricarboxylic acid cycle, whereas increased glutamine uptake serves to replenish the TCA cycle. Furthermore, we found that the PDH flux is maintained by unchanged PDK1 abundance, despite the presence of HIF1. By pharmacological intervention, we demonstrate that the PDH flux is an important node for M(LPS) macrophage activation. Therefore, PDH represents a metabolic intervention point that might become a research target for translational medicine to treat chronic inflammatory diseases.

Particulate Matter from Both Heavy Fuel Oil and Diesel Fuel Shipping Emissions Show Strong Biological Effects on Human Lung Cells at Realistic and Comparable In Vitro Exposure Conditions

Background Ship engine emissions are important with regard to lung and cardiovascular diseases especially in coastal regions worldwide. Known cellular responses to combustion particles include oxidative stress and inflammatory signalling. Objectives To provide a molecular link between the chemical and physical characteristics of ship emission particles and the cellular responses they elicit and to identify potentially harmful fractions in shipping emission aerosols. Methods Through an air-liquid interface exposure system, we exposed human lung cells under realistic in vitro conditions to exhaust fumes from a ship engine running on either common heavy fuel oil (HFO) or cleaner-burning diesel fuel (DF). Advanced chemical analyses of the exhaust aerosols were combined with transcriptional, proteomic and metabolomic profiling including isotope labelling methods to characterise the lung cell responses. Results The HFO emissions contained high concentrations of toxic compounds such as metals and polycyclic aromatic hydrocarbon, and were higher in particle mass. These compounds were lower in DF emissions, which in turn had higher concentrations of elemental carbon (“soot”). Common cellular reactions included cellular stress responses and endocytosis. Reactions to HFO emissions were dominated by oxidative stress and inflammatory responses, whereas DF emissions induced generally a broader biological response than HFO emissions and affected essential cellular pathways such as energy metabolism, protein synthesis, and chromatin modification. Conclusions Despite a lower content of known toxic compounds, combustion particles from the clean shipping fuel DF influenced several essential pathways of lung cell metabolism more strongly than particles from the unrefined fuel HFO. This might be attributable to a higher soot content in DF. Thus the role of diesel soot, which is a known carcinogen in acute air pollution-induced health effects should be further investigated. For the use of HFO and DF we recommend a reduction of carbonaceous soot in the ship emissions by implementation of filtration devices.

Simultaneous extraction of proteins and metabolites from cells in culture

Graphical abstract Three-phase methanol–water–chloroform extraction for biological samples. Examples of components available from each phase are shown. These different phases can be then used for a variety of different analysis methods on different levels of cellular regulation.

Fragment Formula Calculator (FFC): Determination of Chemical Formulas for Fragment Ions in Mass Spectrometric Data

The accurate determination of mass isotopomer distributions (MID) is of great significance for stable isotope-labeling experiments. Most commonly, MIDs are derived from gas chromatography/electron ionization mass spectrometry (GC/EI-MS) measurements. The analysis of fragment ions formed during EI, which contain only specific parts of the original molecule can provide valuable information on the positional distribution of the label. The chemical formula of a fragment ion is usually applied to derive the correction matrix for accurate MID calculation. Hence, the correct assignment of chemical formulas to fragment ions is of crucial importance for correct MIDs. Moreover, the positional distribution of stable isotopes within a fragment ion is of high interest for stable isotope-assisted metabolomics techniques. For example, (13)C-metabolic flux analyses ((13)C-MFA) are dependent on the exact knowledge of the number and position of retained carbon atoms of the unfragmented molecule. Fragment ions containing different carbon atoms are of special interest, since they can carry different flux information. However, the process of mass spectral fragmentation is complex, and identifying the substructures and chemical formulas for these fragment ions is nontrivial. For that reason, we developed an algorithm, based on a systematic bond cleavage, to determine chemical formulas and retained atoms for EI derived fragment ions. Here, we present the fragment formula calculator (FFC) algorithm that can calculate chemical formulas for fragment ions where the chemical bonding (e.g., Lewis structures) of the intact molecule is known. The proposed algorithm is able to cope with general molecular rearrangement reactions occurring during EI in GC/MS measurements. The FFC algorithm is able to integrate stable isotope labeling experiments into the analysis and can automatically exclude candidate formulas that do not fit the observed labeling patterns.1 We applied the FFC algorithm to create a fragment ion repository that contains the chemical formulas and retained carbon atoms of a wide range of trimethylsilyl and tert-butyldimethylsilyl derivatized compounds. In total, we report the chemical formulas and backbone carbon compositions for 160 fragment ions of 43 alkylsilyl-derivatives of primary metabolites. Finally, we implemented the FFC algorithm in an easy-to-use graphical user interface and made it publicly available at http://www.ffc.lu .

Isotope Cluster-Based Compound Matching in Gas Chromatography/Mass Spectrometry for Non-Targeted Metabolomics

Gas chromatography coupled to mass spectrometry (GC/MS) has emerged as a powerful tool in metabolomics studies. A major bottleneck in current data analysis of GC/MS-based metabolomics studies is compound matching and identification, as current methods generate high rates of false positive and false-negative identifications. This is especially true for data sets containing a high amount of noise. In this work, a novel spectral similarity measure based on the specific fragmentation patterns of electron impact mass spectra is proposed. An important aspect of these algorithmic methods is the handling of noisy data. The performance of the proposed method compared to the dot product, the current gold standard, was evaluated on a complex biological data set. The analysis results showed significant improvements of the proposed method in compound matching and chromatogram alignment compared to the dot product.

Metabolic Profiling as Well as Stable Isotope Assisted Metabolic and Proteomic Analysis of RAW 264.7 Macrophages Exposed to Ship Engine Aerosol Emissions: Different Effects of Heavy Fuel Oil and Refined Diesel Fuel.

Exposure to air pollution resulting from fossil fuel combustion has been linked to multiple short-term and long term health effects. In a previous study, exposure of lung epithelial cells to engine exhaust from heavy fuel oil (HFO) and diesel fuel (DF), two of the main fuels used in marine engines, led to an increased regulation of several pathways associated with adverse cellular effects, including pro-inflammatory pathways. In addition, DF exhaust exposure was shown to have a wider response on multiple cellular regulatory levels compared to HFO emissions, suggesting a potentially higher toxicity of DF emissions over HFO. In order to further understand these effects, as well as to validate these findings in another cell line, we investigated macrophages under the same conditions as a more inflammation-relevant model. An air-liquid interface aerosol exposure system was used to provide a more biologically relevant exposure system compared to submerged experiments, with cells exposed to either the complete aerosol (particle and gas phase), or the gas phase only (with particles filtered out). Data from cytotoxicity assays were integrated with metabolomics and proteomics analyses, including stable isotope-assisted metabolomics, in order to uncover pathways affected by combustion aerosol exposure in macrophages. Through this approach, we determined differing phenotypic effects associated with the different components of aerosol. The particle phase of diluted combustion aerosols was found to induce increased cell death in macrophages, while the gas phase was found more to affect the metabolic profile. In particular, a higher cytotoxicity of DF aerosol emission was observed in relation to the HFO aerosol. Furthermore, macrophage exposure to the gas phase of HFO leads to an induction of a pro-inflammatory metabolic and proteomic phenotype. These results validate the effects found in lung epithelial cells, confirming the role of inflammation and cellular stress in the response to combustion aerosols.

Bridging the gap between non-targeted stable isotope labeling and metabolic flux analysis

BackgroundMetabolism gained increasing interest for the understanding of diseases and to pinpoint therapeutic intervention points. However, classical metabolomics techniques only provide a very static view on metabolism. Metabolic flux analysis methods, on the other hand, are highly targeted and require detailed knowledge on metabolism beforehand.ResultsWe present a novel workflow to analyze non-targeted metabolome-wide stable isotope labeling data to detect metabolic flux changes in a non-targeted manner. Furthermore, we show how similarity-analysis of isotopic enrichment patterns can be used for pathway contextualization of unidentified compounds. We illustrate our approach with the analysis of changes in cellular metabolism of human adenocarcinoma cells in response to decreased oxygen availability. Starting without a priori knowledge, we detect metabolic flux changes, leading to an increased glutamine contribution to acetyl-CoA production, reveal biosynthesis of N-acetylaspartate by N-acetyltransferase 8-like (NAT8L) in lung cancer cells and show that NAT8L silencing inhibits proliferation of A549, JHH-4, PH5CH8, and BEAS-2B cells.ConclusionsDifferential stable isotope labeling analysis provides qualitative metabolic flux information in a non-targeted manner. Furthermore, similarity analysis of enrichment patterns provides information on metabolically closely related compounds. N-acetylaspartate and NAT8L are important players in cancer cell metabolism, a context in which they have not received much attention yet.

Branched‐chain ketoacids secreted by glioblastoma cells via MCT1 modulate macrophage phenotype

Elevated amino acid catabolism is common to many cancers. Here, we show that glioblastoma are excreting large amounts of branched‐chain ketoacids (BCKAs), metabolites of branched‐chain amino acid (BCAA) catabolism. We show that efflux of BCKAs, as well as pyruvate, is mediated by the monocarboxylate transporter 1 (MCT1) in glioblastoma. MCT1 locates in close proximity to BCKA‐generating branched‐chain amino acid transaminase 1, suggesting possible functional interaction of the proteins. Using in vitro models, we demonstrate that tumor‐excreted BCKAs can be taken up and re‐aminated to BCAAs by tumor‐associated macrophages. Furthermore, exposure to BCKAs reduced the phagocytic activity of macrophages. This study provides further evidence for the eminent role of BCAA catabolism in glioblastoma by demonstrating that tumor‐excreted BCKAs might have a direct role in tumor immune suppression. Our data further suggest that the anti‐proliferative effects of MCT1 knockdown observed by others might be related to the blocked excretion of BCKAs.