Analyzing postprandial metabolomics data using multiway models: a simulation study.

BACKGROUND: Analysis of time-resolved postprandial metabolomics data can improve the understanding of metabolic mechanisms, potentially revealing biomarkers for early diagnosis of metabolic diseases and advancing precision nutrition and medicine. Postprandial metabolomics measurements at several time points from multiple subjects can be arranged as a subjects by metabolites by time points array. Traditional analysis methods are limited in terms of revealing subject groups, related metabolites, and temporal patterns simultaneously from such three-way data. RESULTS: We introduce an unsupervised multiway analysis approach based on the CANDECOMP/PARAFAC (CP) model for improved analysis of postprandial metabolomics data guided by a simulation study. Because of the lack of ground truth in real data, we generate simulated data using a comprehensive human metabolic model. This allows us to assess the performance of CP models in terms of revealing subject groups and underlying metabolic processes. We study three analysis approaches: analysis of fasting-state data using principal component analysis, T0-corrected data (i.e., data corrected by subtracting fasting-state data) using a CP model and full-dynamic (i.e., full postprandial) data using CP. Through extensive simulations, we demonstrate that CP models capture meaningful and stable patterns from simulated meal challenge data, revealing underlying mechanisms and differences between diseased versus healthy groups. CONCLUSIONS: Our experiments show that it is crucial to analyze both fasting-state and T0-corrected data for understanding metabolic differences among subject groups. Depending on the nature of the subject group structure, the best group separation may be achieved by CP models of T0-corrected or full-dynamic data. This study introduces an improved analysis approach for postprandial metabolomics data while also shedding light on the debate about correcting baseline values in longitudinal data analysis.

Personalised modelling of clinical heterogeneity between medium-chain acyl-CoA dehydrogenase patients.

BACKGROUND: Monogenetic inborn errors of metabolism cause a wide phenotypic heterogeneity that may even differ between family members carrying the same genetic variant. Computational modelling of metabolic networks may identify putative sources of this inter-patient heterogeneity. Here, we mainly focus on medium-chain acyl-CoA dehydrogenase deficiency (MCADD), the most common inborn error of the mitochondrial fatty acid oxidation (mFAO). It is an enigma why some MCADD patients-if untreated-are at risk to develop severe metabolic decompensations, whereas others remain asymptomatic throughout life. We hypothesised that an ability to maintain an increased free mitochondrial CoA (CoASH) and pathway flux might distinguish asymptomatic from symptomatic patients. RESULTS: We built and experimentally validated, for the first time, a kinetic model of the human liver mFAO. Metabolites were partitioned according to their water solubility between the bulk aqueous matrix and the inner membrane. Enzymes are also either membrane-bound or in the matrix. This metabolite partitioning is a novel model attribute and improved predictions. MCADD substantially reduced pathway flux and CoASH, the latter due to the sequestration of CoA as medium-chain acyl-CoA esters. Analysis of urine from MCADD patients obtained during a metabolic decompensation showed an accumulation of medium- and short-chain acylcarnitines, just like the acyl-CoA pool in the MCADD model. The model suggested some rescues that increased flux and CoASH, notably increasing short-chain acyl-CoA dehydrogenase (SCAD) levels. Proteome analysis of MCADD patient-derived fibroblasts indeed revealed elevated levels of SCAD in a patient with a clinically asymptomatic state. This is a rescue for MCADD that has not been explored before. Personalised models based on these proteomics data confirmed an increased pathway flux and CoASH in the model of an asymptomatic patient compared to those of symptomatic MCADD patients. CONCLUSIONS: We present a detailed, validated kinetic model of mFAO in human liver, with solubility-dependent metabolite partitioning. Personalised modelling of individual patients provides a novel explanation for phenotypic heterogeneity among MCADD patients. Further development of personalised metabolic models is a promising direction to improve individualised risk assessment, management and monitoring for inborn errors of metabolism.

Hyperglycaemia, pregnancy outcomes and maternal metabolic disease risk during pregnancy and lactation in a lean gestational diabetes mouse model.

Hyperglycaemia in pregnancy (HIP) is a pregnancy complication characterized by mild to moderate hyperglycaemia that negatively impacts short- and long-term health of mother and child. However, relationships between severity and timing of pregnancy hyperglycaemia and postpartum outcomes have not been systemically investigated. We investigated the impact of hyperglycaemia developing during pregnancy (gestational diabetes mellitus, GDM) or already present pre-mating (pre-gestational diabetes mellitus, PDM) on maternal health and pregnancy outcomes. GDM and PDM were induced in C57BL/6NTac mice by combined 60% high fat diet (HF) and low dose streptozotocin (STZ). Animals were screened for PDM prior to mating, and all underwent an oral glucose tolerance test on gestational day (GD)15. Tissues were collected at GD18 or at postnatal day (PN)15. Among HFSTZ-treated dams, 34% developed PDM and 66% developed GDM, characterized by impaired glucose-induced insulin release and inadequate suppression of endogenous glucose production. No increased adiposity or overt insulin resistance was observed. Furthermore, markers of non-alcoholic fatty liver disease (NAFLD) were significantly increased in PDM at GD18 and were positively correlated with basal glucose levels at GD18 in GDM dams. By PN15, NAFLD markers were also increased in GDM dams. Only PDM affected pregnancy outcomes such as litter size. Our findings indicate that GDM and PDM, resulting in disturbances of maternal glucose homeostasis, increase the risk of postpartum NAFLD development, related to the onset and severity of pregnancy hyperglycaemia. These findings signal a need for earlier monitoring of maternal glycaemia and more rigorous follow-up of maternal health after GDM and PDM pregnancy in humans. KEY POINTS: We studied the impact of high-fat diet/streptozotocin induced hyperglycaemia in pregnancy in mice and found that this impaired glucose tolerance and insulin release. Litter size and embryo survival were compromised by pre-gestational, but not by gestational, diabetes. Despite postpartum recovery from hyperglycaemia in a majority of dams, liver disease markers were further elevated by postnatal day 15. Maternal liver disease markers were associated with the severity of hyperglycaemia at gestational day 18. The association between hyperglycaemic exposure and non-alcoholic fatty liver disease signals a need for more rigorous monitoring and follow-up of maternal glycaemia and health in diabetic pregnancy in humans.

Quantitative analysis of amino acid metabolism in liver cancer links glutamate excretion to nucleotide synthesis.

Many cancer cells consume glutamine at high rates; counterintuitively, they simultaneously excrete glutamate, the first intermediate in glutamine metabolism. Glutamine consumption has been linked to replenishment of tricarboxylic acid cycle (TCA) intermediates and synthesis of adenosine triphosphate (ATP), but the reason for glutamate excretion is unclear. Here, we dynamically profile the uptake and excretion fluxes of a liver cancer cell line (HepG2) and use genome-scale metabolic modeling for in-depth analysis. We find that up to 30% of the glutamine is metabolized in the cytosol, primarily for nucleotide synthesis, producing cytosolic glutamate. We hypothesize that excreting glutamate helps the cell to increase the nucleotide synthesis rate to sustain growth. Indeed, we show experimentally that partial inhibition of glutamate excretion reduces cell growth. Our integrative approach thus links glutamine addiction to glutamate excretion in cancer and points toward potential drug targets.

Bistability in fatty-acid oxidation resulting from substrate inhibition.

In this study we demonstrated through analytic considerations and numerical studies that the mitochondrial fatty-acid ß-oxidation can exhibit bistable-hysteresis behavior. In an experimentally validated computational model we identified a specific region in the parameter space in which two distinct stable and one unstable steady state could be attained with different fluxes. The two stable states were referred to as low-flux (disease) and high-flux (healthy) state. By a modular kinetic approach we traced the origin and causes of the bistability back to the distributive kinetics and the conservation of CoA, in particular in the last rounds of the ß-oxidation. We then extended the model to investigate various interventions that may confer health benefits by activating the pathway, including (i) activation of the last enzyme MCKAT via its endogenous regulator p46-SHC protein, (ii) addition of a thioesterase (an acyl-CoA hydrolysing enzyme) as a safety valve, and (iii) concomitant activation of a number of upstream and downstream enzymes by short-chain fatty-acids (SCFA), metabolites that are produced from nutritional fibers in the gut. A high concentration of SCFAs, thioesterase activity, and inhibition of the p46Shc protein led to a disappearance of the bistability, leaving only the high-flux state. A better understanding of the switch behavior of the mitochondrial fatty-acid oxidation process between a low- and a high-flux state may lead to dietary and pharmacological intervention in the treatment or prevention of obesity and or non-alcoholic fatty-liver disease.

Age-related susceptibility to insulin resistance arises from a combination of CPT1B decline and lipid overload.

BACKGROUND: The skeletal muscle plays a central role in glucose homeostasis through the uptake of glucose from the extracellular medium in response to insulin. A number of factors are known to disrupt the normal response to insulin leading to the emergence of insulin resistance (IR). Advanced age and a high-fat diet are factors that increase the susceptibility to IR, with lipid accumulation in the skeletal muscle being a key driver of this phenomenon. It is debated, however, whether lipid accumulation arises due to dietary lipid overload or from a decline of mitochondrial function. To gain insights into the interplay of diet and age in the flexibility of muscle lipid and glucose handling, we combined lipidomics, proteomics, mitochondrial function analysis and computational modelling to investigate young and aged mice on a low- or high-fat diet (HFD). RESULTS: As expected, aged mice were more susceptible to IR when given a HFD than young mice. The HFD induced intramuscular lipid accumulation specifically in aged mice, including C18:0-containing ceramides and diacylglycerols. This was reflected by the mitochondrial ß-oxidation capacity, which was upregulated by the HFD in young, but not in old mice. Conspicuously, most ß-oxidation proteins were upregulated by the HFD in both groups, but carnitine palmitoyltransferase 1B (CPT1B) declined in aged animals. Computational modelling traced the flux control mostly to CPT1B, suggesting a CPT1B-driven loss of flexibility to the HFD with age. Finally, in old animals, glycolytic protein levels were reduced and less flexible to the diet. CONCLUSION: We conclude that intramuscular lipid accumulation and decreased insulin sensitivity are not due to age-related mitochondrial dysfunction or nutritional overload alone, but rather to their combined effects. Moreover, we identify CPT1B as a potential target to counteract age-dependent intramuscular lipid accumulation and thereby IR.

Pyruvate Dehydrogenase Kinase Inhibition by Dichloroacetate in Melanoma Cells Unveils Metabolic Vulnerabilities.

Melanoma is characterized by high glucose uptake, partially mediated through elevated pyruvate dehydrogenase kinase (PDK), making PDK a potential treatment target in melanoma. We aimed to reduce glucose uptake in melanoma cell lines through PDK inhibitors dichloroacetate (DCA) and AZD7545 and through PDK knockdown, to inhibit cell growth and potentially unveil metabolic co-vulnerabilities resulting from PDK inhibition. MeWo cells were most sensitive to DCA, while SK-MEL-2 was the least sensitive, with IC50 values ranging from 13.3 to 27.0 mM. DCA strongly reduced PDH phosphorylation and increased the oxygen consumption rate:extracellular acidification rate (OCR:ECAR) ratio up to 6-fold. Knockdown of single PDK isoforms had similar effects on PDH phosphorylation and OCR:ECAR ratio as DCA but did not influence sensitivity to DCA. Growth inhibition by DCA was synergistic with the glutaminase inhibitor CB-839 (2- to 5-fold sensitization) and with diclofenac, known to inhibit monocarboxylate transporters (MCTs) (3- to 8-fold sensitization). CB-839 did not affect the OCR:ECAR response to DCA, whereas diclofenac strongly inhibited ECAR and further increased the OCR:ECAR ratio. We conclude that in melanoma cell lines, DCA reduces proliferation through reprogramming of cellular metabolism and synergizes with other metabolically targeted drugs.

Simultaneous Quantification of the Concentration and Carbon Isotopologue Distribution of Polar Metabolites in a Single Analysis by Gas Chromatography and Mass Spectrometry.

13C-isotope tracing is a frequently employed approach to study metabolic pathway activity. When combined with the subsequent quantification of absolute metabolite concentrations, this enables detailed characterization of the metabolome in biological specimens and facilitates computational time-resolved flux quantification. Classically, a 13C-isotopically labeled sample is required to quantify 13C-isotope enrichments and a second unlabeled sample for the quantification of metabolite concentrations. The rationale for a second unlabeled sample is that the current methods for metabolite quantification rely mostly on isotope dilution mass spectrometry (IDMS) and thus isotopically labeled internal standards are added to the unlabeled sample. This excludes the absolute quantification of metabolite concentrations in 13C-isotopically labeled samples. To address this issue, we have developed and validated a new strategy using an unlabeled internal standard to simultaneously quantify metabolite concentrations and 13C-isotope enrichments in a single 13C-labeled sample based on gas chromatography-mass spectrometry (GC/MS). The method was optimized for amino acids and citric acid cycle intermediates and was shown to have high analytical precision and accuracy. Metabolite concentrations could be quantified in small tissue samples (≥20 mg). Also, we applied the method on 13C-isotopically labeled mammalian cells treated with and without a metabolic inhibitor. We proved that we can quantify absolute metabolite concentrations and 13C-isotope enrichments in a single 13C-isotopically labeled sample.

A Proinflammatory Gut Microbiota Increases Systemic Inflammation and Accelerates Atherosclerosis.

RATIONALE: Several studies have suggested a role for the gut microbiota in inflammation and atherogenesis. A causal relation relationship between gut microbiota, inflammation, and atherosclerosis has not been explored previously. OBJECTIVE: Here, we investigated whether a proinflammatory microbiota from Caspase1-/- ( Casp1-/-) mice accelerates atherogenesis in Ldlr-/- mice. METHOD AND RESULTS: We treated female Ldlr-/- mice with antibiotics and subsequently transplanted them with fecal microbiota from Casp1-/- mice based on a cohousing approach. Autologous transplantation of fecal microbiota of Ldlr-/- mice served as control. Mice were cohoused for 8 or 13 weeks and fed chow or high-fat cholesterol-rich diet. Fecal samples were collected, and factors related to inflammation, metabolism, intestinal health, and atherosclerotic phenotypes were measured. Unweighted Unifrac distances of 16S rDNA (ribosomal DNA) sequences confirmed the introduction of the Casp1-/- and Ldlr-/- microbiota into Ldlr-/- mice (referred to as Ldlr-/-( Casp1-/-) or Ldlr-/-( Ldlr-/-) mice). Analysis of atherosclerotic lesion size in the aortic root demonstrated a significant 29% increase in plaque size in 13-week high-fat cholesterol-fed Ldlr-/-( Casp1-/-) mice compared with Ldlr-/-( Ldlr-/-) mice. We found increased numbers of circulating monocytes and neutrophils and elevated proinflammatory cytokine levels in plasma in high-fat cholesterol-fed Ldlr-/-( Casp1-/-) compared with Ldlr-/-( Ldlr-/-) mice. Neutrophil accumulation in the aortic root of Ldlr-/-( Casp1-/-) mice was enhanced compared with Ldlr-/-( Ldlr-/-) mice. 16S-rDNA-encoding sequence analysis in feces identified a significant reduction in the short-chain fatty acid-producing taxonomies Akkermansia, Christensenellaceae, Clostridium, and Odoribacter in Ldlr-/-( Casp1-/-) mice. Consistent with these findings, cumulative concentrations of the anti-inflammatory short-chain fatty acids propionate, acetate and butyrate in the cecum were significantly reduced in 13-week high-fat cholesterol-fed Ldlr-/-( Casp1-/-) compared with Ldlr-/-( Ldlr-/-) mice. CONCLUSIONS: Introduction of the proinflammatory Casp1-/- microbiota into Ldlr-/- mice enhances systemic inflammation and accelerates atherogenesis.

Targeted Proteomics to Study Mitochondrial Biology.

Targeted mass spectrometry in the selected or parallel reaction monitoring (SRM or PRM) mode is a widely used methodology to quantify proteins based on so-called signature or proteotypic peptides. SRM has the advantage of being able to quantify a range of proteins in a single analysis, for example, to measure the level of enzymes comprising a biochemical pathway. In this chapter, we will detail how to set up an SRM assay on the example of the mitochondrial protein succinate dehydrogenase [ubiquinone] flavoprotein subunit (mouse UniProt-code Q8K2B3). First, we will outline the in silico assay design including the choice of peptides based on a range of properties. We will further delineate different quantification strategies and introduce the reader to LC-MS assay development including the selection of the optimal peptide charge state and fragment ions as well as a discussion of the dynamic range of detection. The chapter will close with an application from the area of mitochondrial biology related to the quantification of a set of proteins isolated from mouse liver mitochondria in a study on mitochondrial respiratory flux decline in aging mouse muscle.

The promiscuous enzyme medium-chain 3-keto-acyl-CoA thiolase triggers a vicious cycle in fatty-acid beta-oxidation.

Mitochondrial fatty-acid beta-oxidation (mFAO) plays a central role in mammalian energy metabolism. Multiple severe diseases are associated with defects in this pathway. Its kinetic structure is characterized by a complex wiring of which the functional implications have hardly been explored. Repetitive cycles of reversible reactions, each cycle shortening the fatty acid by two carbon atoms, evoke competition between intermediates of different chain lengths for a common set of 'promiscuous' enzymes (enzymes with activity towards multiple substrates). In our validated kinetic model of the pathway, substrate overload causes a steep and detrimental flux decline. Here, we unravel the underlying mechanism and the role of enzyme promiscuity in it. Comparison of alternative model versions elucidated the role of promiscuity of individual enzymes. Promiscuity of the last enzyme of the pathway, medium-chain ketoacyl-CoA thiolase (MCKAT), was both necessary and sufficient to elicit the flux decline. Subsequently, Metabolic Control Analysis revealed that MCKAT had insufficient capacity to cope with high substrate influx. Next, we quantified the internal metabolic regulation, revealing a vicious cycle around MCKAT. Upon substrate overload, MCKAT's ketoacyl-CoA substrates started to accumulate. The unfavourable equilibrium constant of the preceding enzyme, medium/short-chain hydroxyacyl-CoA dehydrogenase, worked as an amplifier, leading to accumulation of upstream CoA esters, including acyl-CoA esters. These acyl-CoA esters are at the same time products of MCKAT and inhibited its already low activity further. Finally, the accumulation of CoA esters led to a sequestration of free CoA. CoA being a cofactor for MCKAT, its sequestration limited the MCKAT activity even further, thus completing the vicious cycle. Since CoA is also a substrate for distant enzymes, it efficiently communicated the 'traffic jam' at MCKAT to the entire pathway. This novel mechanism provides a basis to explore the role of mFAO in disease and elucidate similar principles in other pathways of lipid metabolism.

Living on the edge: substrate competition explains loss of robustness in mitochondrial fatty-acid oxidation disorders.

BACKGROUND: Defects in genes involved in mitochondrial fatty-acid oxidation (mFAO) reduce the ability of patients to cope with metabolic challenges. mFAO enzymes accept multiple substrates of different chain length, leading to molecular competition among the substrates. Here, we combined computational modeling with quantitative mouse and patient data to investigate whether substrate competition affects pathway robustness in mFAO disorders. RESULTS: First, we used comprehensive biochemical analyses of wild-type mice and mice deficient for medium-chain acyl-CoA dehydrogenase (MCAD) to parameterize a detailed computational model of mFAO. Model simulations predicted that MCAD deficiency would have no effect on the pathway flux at low concentrations of the mFAO substrate palmitoyl-CoA. However, high concentrations of palmitoyl-CoA would induce a decline in flux and an accumulation of intermediate metabolites. We proved computationally that the predicted overload behavior was due to substrate competition in the pathway. Second, to study the clinical relevance of this mechanism, we used patients' metabolite profiles and generated a humanized version of the computational model. While molecular competition did not affect the plasma metabolite profiles during MCAD deficiency, it was a key factor in explaining the characteristic acylcarnitine profiles of multiple acyl-CoA dehydrogenase deficient patients. The patient-specific computational models allowed us to predict the severity of the disease phenotype, providing a proof of principle for the systems medicine approach. CONCLUSION: We conclude that substrate competition is at the basis of the physiology seen in patients with mFAO disorders, a finding that may explain why these patients run a risk of a life-threatening metabolic catastrophe.

Translational Targeted Proteomics Profiling of Mitochondrial Energy Metabolic Pathways in Mouse and Human Samples.

Absolute measurements of protein abundance are important in the understanding of biological processes and the precise computational modeling of biological pathways. We developed targeted LC-MS/MS assays in the selected reaction monitoring (SRM) mode to quantify over 50 mitochondrial proteins in a single run. The targeted proteins cover the tricarboxylic acid cycle, fatty acid ß-oxidation, oxidative phosphorylation, and the detoxification of reactive oxygen species. Assays used isotopically labeled concatemers as internal standards designed to target murine mitochondrial proteins and their human orthologues. Most assays were also suitable to quantify the corresponding protein orthologues in rats. After exclusion of peptides that did not pass the selection criteria, we arrived at SRM assays for 55 mouse, 52 human, and 51 rat proteins. These assays were optimized in isolated mitochondrial fractions from mouse and rat liver and cultured human fibroblasts and in total liver extracts from mouse, rat, and human. The developed proteomics approach is suitable for the quantification of proteins in the mitochondrial energy metabolic pathways in mice, rats, and humans as a basis for translational research. Initial data show that the assays have great potential for elucidating the adaptive response of human patients to mutations in mitochondrial proteins in a clinical setting.

Malnutrition-associated liver steatosis and ATP depletion is caused by peroxisomal and mitochondrial dysfunction.

BACKGROUND & AIMS: Severe malnutrition in young children is associated with signs of hepatic dysfunction such as steatosis and hypoalbuminemia, but its etiology is unknown. Peroxisomes and mitochondria play key roles in various hepatic metabolic functions including lipid metabolism and energy production. To investigate the involvement of these organelles in the mechanisms underlying malnutrition-induced hepatic dysfunction we developed a rat model of malnutrition. METHODS: Weanling rats were placed on a low protein or control diet (5% or 20% of calories from protein, respectively) for four weeks. Peroxisomal and mitochondrial structural features were characterized using immunofluorescence and electron microscopy. Mitochondrial function was assessed using high-resolution respirometry. A novel targeted quantitative proteomics method was applied to analyze 47 mitochondrial proteins involved in oxidative phosphorylation, tricarboxylic acid cycle and fatty acid ß-oxidation pathways. RESULTS: Low protein diet-fed rats developed hypoalbuminemia and hepatic steatosis, consistent with the human phenotype. Hepatic peroxisome content was decreased and metabolomic analysis indicated peroxisomal dysfunction. This was followed by changes in mitochondrial ultrastructure and increased mitochondrial content. Mitochondrial function was impaired due to multiple defects affecting respiratory chain complex I and IV, pyruvate uptake and several ß-oxidation enzymes, leading to strongly reduced hepatic ATP levels. Fenofibrate supplementation restored hepatic peroxisome abundance and increased mitochondrial ß-oxidation capacity, resulting in reduced steatosis and normalization of ATP and plasma albumin levels. CONCLUSIONS: Malnutrition leads to severe impairments in hepatic peroxisomal and mitochondrial function, and hepatic metabolic dysfunction. We discuss the potential future implications of our findings for the clinical management of malnourished children. LAY SUMMARY: Severe malnutrition in children is associated with metabolic disturbances that are poorly understood. In order to study this further, we developed a malnutrition animal model and found that severe malnutrition leads to an impaired function of liver mitochondria which are essential for energy production and a loss of peroxisomes, which are important for normal liver metabolic function.

Transcriptome-wide analysis of trypanosome mRNA decay reveals complex degradation kinetics and suggests a role for co-transcriptional degradation in determining mRNA levels.

African trypanosomes are an excellent system for quantitative modelling of post-transcriptional mRNA control. Transcription is constitutive and polycistronic; individual mRNAs are excised by trans splicing and polyadenylation. We here measure mRNA decay kinetics in two life cycle stages, bloodstream and procyclic forms, by transcription inhibition and RNASeq. Messenger RNAs with short half-lives tend to show initial fast degradation, followed by a slower phase; they are often stabilized by depletion of the 5'-3' exoribonuclease XRNA. Many longer-lived mRNAs show initial slow degradation followed by rapid destruction: we suggest that the slow phase reflects gradual deadenylation. Developmentally regulated mRNAs often show regulated decay, and switch their decay pattern. Rates of mRNA decay are good predictors of steady state levels for short mRNAs, but mRNAs longer than 3 kb show unexpectedly low abundances. Modelling shows that variations in splicing and polyadenylation rates can contribute to steady-state mRNA levels, but this is completely dependent on competition between processing and co-transcriptional mRNA precursor destruction.

Drug target identification through systems biology.

To rationalise drug target selection, we should understand the role of putative targets in biological pathways quantitatively. We review here how experimental and computational network-based approaches can aid more rational drug target selection and illustrate this with results obtained for microbes and for cancer. Comparison of the drug response of biochemical networks in target cells and (healthy) host cells can reveal network-selective targets.

Dissecting the catalytic mechanism of Trypanosoma brucei trypanothione synthetase by kinetic analysis and computational modeling.

In pathogenic trypanosomes, trypanothione synthetase (TryS) catalyzes the synthesis of both glutathionylspermidine (Gsp) and trypanothione (bis(glutathionyl)spermidine (T(SH)2)). Here we present a thorough kinetic analysis of Trypanosoma brucei TryS in a newly developed phosphate buffer system at pH 7.0 and 37 °C, mimicking the physiological environment of the enzyme in the cytosol of bloodstream parasites. Under these conditions, TryS displays Km values for GSH, ATP, spermidine, and Gsp of 34, 18, 687, and 32 µm, respectively, as well as Ki values for GSH and T(SH)2 of 1 mm and 360 µm, respectively. As Gsp hydrolysis has a Km value of 5.6 mm, the in vivo amidase activity is probably negligible. To obtain deeper insight in the molecular mechanism of TryS, we have formulated alternative kinetic models, with elementary reaction steps represented by linear kinetic equations. The model parameters were fitted to the extensive matrix of steady-state data obtained for different substrate/product combinations under the in vivo-like conditions. The best model describes the full kinetic profile and is able to predict time course data that were not used for fitting. This system's biology approach to enzyme kinetics led us to conclude that (i) TryS follows a ter-reactant mechanism, (ii) the intermediate Gsp dissociates from the enzyme between the two catalytic steps, and (iii) T(SH)2 inhibits the enzyme by remaining bound at its product site and, as does the inhibitory GSH, by binding to the activated enzyme complex. The newly detected concerted substrate and product inhibition suggests that TryS activity is tightly regulated.

Biochemical competition makes fatty-acid ß-oxidation vulnerable to substrate overload.

Fatty-acid metabolism plays a key role in acquired and inborn metabolic diseases. To obtain insight into the network dynamics of fatty-acid ß-oxidation, we constructed a detailed computational model of the pathway and subjected it to a fat overload condition. The model contains reversible and saturable enzyme-kinetic equations and experimentally determined parameters for rat-liver enzymes. It was validated by adding palmitoyl CoA or palmitoyl carnitine to isolated rat-liver mitochondria: without refitting of measured parameters, the model correctly predicted the ß-oxidation flux as well as the time profiles of most acyl-carnitine concentrations. Subsequently, we simulated the condition of obesity by increasing the palmitoyl-CoA concentration. At a high concentration of palmitoyl CoA the ß-oxidation became overloaded: the flux dropped and metabolites accumulated. This behavior originated from the competition between acyl CoAs of different chain lengths for a set of acyl-CoA dehydrogenases with overlapping substrate specificity. This effectively induced competitive feedforward inhibition and thereby led to accumulation of CoA-ester intermediates and depletion of free CoA (CoASH). The mitochondrial [NAD⁺]/[NADH] ratio modulated the sensitivity to substrate overload, revealing a tight interplay between regulation of ß-oxidation and mitochondrial respiration.

Handling uncertainty in dynamic models: the pentose phosphate pathway in Trypanosoma brucei.

Dynamic models of metabolism can be useful in identifying potential drug targets, especially in unicellular organisms. A model of glycolysis in the causative agent of human African trypanosomiasis, Trypanosoma brucei, has already shown the utility of this approach. Here we add the pentose phosphate pathway (PPP) of T. brucei to the glycolytic model. The PPP is localized to both the cytosol and the glycosome and adding it to the glycolytic model without further adjustments leads to a draining of the essential bound-phosphate moiety within the glycosome. This phosphate "leak" must be resolved for the model to be a reasonable representation of parasite physiology. Two main types of theoretical solution to the problem could be identified: (i) including additional enzymatic reactions in the glycosome, or (ii) adding a mechanism to transfer bound phosphates between cytosol and glycosome. One example of the first type of solution would be the presence of a glycosomal ribokinase to regenerate ATP from ribose 5-phosphate and ADP. Experimental characterization of ribokinase in T. brucei showed that very low enzyme levels are sufficient for parasite survival, indicating that other mechanisms are required in controlling the phosphate leak. Examples of the second type would involve the presence of an ATP:ADP exchanger or recently described permeability pores in the glycosomal membrane, although the current absence of identified genes encoding such molecules impedes experimental testing by genetic manipulation. Confronted with this uncertainty, we present a modeling strategy that identifies robust predictions in the context of incomplete system characterization. We illustrate this strategy by exploring the mechanism underlying the essential function of one of the PPP enzymes, and validate it by confirming the model predictions experimentally.

The paradox of fatty-acid ß-oxidation in muscle insulin resistance: Metabolic control and muscle heterogeneity.

The skeletal muscle is a metabolically heterogeneous tissue that plays a key role in maintaining whole-body glucose homeostasis. It is well known that muscle insulin resistance (IR) precedes the development of type 2 diabetes. There is a consensus that the accumulation of specific lipid species in the tissue can drive IR. However, the role of the mitochondrial fatty-acid ß-oxidation in IR and, consequently, in the control of glucose uptake remains paradoxical: interventions that either inhibit or activate fatty-acid ß-oxidation have been shown to prevent IR. We here discuss the current theories and evidence for the interplay between ß-oxidation and glucose uptake in IR. To address the underlying intricacies, we (1) dive into the control of glucose uptake fluxes into muscle tissues using the framework of Metabolic Control Analysis, and (2) disentangle concepts of flux and catalytic capacities taking into account skeletal muscle heterogeneity. Finally, we speculate about hitherto unexplored mechanisms that could bring contrasting evidence together. Elucidating how ß-oxidation is connected to muscle IR and the underlying role of muscle heterogeneity enhances disease understanding and paves the way for new treatments for type 2 diabetes.