Interoperable and scalable data analysis with microservices: applications in metabolomics.

MOTIVATION: Developing a robust and performant data analysis workflow that integrates all necessary components whilst still being able to scale over multiple compute nodes is a challenging task. We introduce a generic method based on the microservice architecture, where software tools are encapsulated as Docker containers that can be connected into scientific workflows and executed using the Kubernetes container orchestrator. RESULTS: We developed a Virtual Research Environment (VRE) which facilitates rapid integration of new tools and developing scalable and interoperable workflows for performing metabolomics data analysis. The environment can be launched on-demand on cloud resources and desktop computers. IT-expertise requirements on the user side are kept to a minimum, and workflows can be re-used effortlessly by any novice user. We validate our method in the field of metabolomics on two mass spectrometry, one nuclear magnetic resonance spectroscopy and one fluxomics study. We showed that the method scales dynamically with increasing availability of computational resources. We demonstrated that the method facilitates interoperability using integration of the major software suites resulting in a turn-key workflow encompassing all steps for mass-spectrometry-based metabolomics including preprocessing, statistics and identification. Microservices is a generic methodology that can serve any scientific discipline and opens up for new types of large-scale integrative science. AVAILABILITY AND IMPLEMENTATION: The PhenoMeNal consortium maintains a web portal (https://portal.phenomenal-h2020.eu) providing a GUI for launching the Virtual Research Environment. The GitHub repository https://github.com/phnmnl/ hosts the source code of all projects. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

p13CMFA: Parsimonious 13C metabolic flux analysis.

Deciphering the mechanisms of regulation of metabolic networks subjected to perturbations, including disease states and drug-induced stress, relies on tracing metabolic fluxes. One of the most informative data to predict metabolic fluxes are 13C based metabolomics, which provide information about how carbons are redistributed along central carbon metabolism. Such data can be integrated using 13C Metabolic Flux Analysis (13C MFA) to provide quantitative metabolic maps of flux distributions. However, 13C MFA might be unable to reduce the solution space towards a unique solution either in large metabolic networks or when small sets of measurements are integrated. Here we present parsimonious 13C MFA (p13CMFA), an approach that runs a secondary optimization in the 13C MFA solution space to identify the solution that minimizes the total reaction flux. Furthermore, flux minimization can be weighted by gene expression measurements allowing seamless integration of gene expression data with 13C data. As proof of concept, we demonstrate how p13CMFA can be used to estimate intracellular flux distributions from 13C measurements and transcriptomics data. We have implemented p13CMFA in Iso2Flux, our in-house developed isotopic steady-state 13C MFA software. The source code is freely available on GitHub (https://github.com/cfoguet/iso2flux/releases/tag/0.7.2).

A key role for mitochondrial gatekeeper pyruvate dehydrogenase in oncogene-induced senescence.

In response to tenacious stress signals, such as the unscheduled activation of oncogenes, cells can mobilize tumour suppressor networks to avert the hazard of malignant transformation. A large body of evidence indicates that oncogene-induced senescence (OIS) acts as such a break, withdrawing cells from the proliferative pool almost irreversibly, thus crafting a vital pathophysiological mechanism that protects against cancer. Despite the widespread contribution of OIS to the cessation of tumorigenic expansion in animal models and humans, we have only just begun to define the underlying mechanism and identify key players. Although deregulation of metabolism is intimately linked to the proliferative capacity of cells, and senescent cells are thought to remain metabolically active, little has been investigated in detail about the role of cellular metabolism in OIS. Here we show, by metabolic profiling and functional perturbations, that the mitochondrial gatekeeper pyruvate dehydrogenase (PDH) is a crucial mediator of senescence induced by BRAF(V600E), an oncogene commonly mutated in melanoma and other cancers. BRAF(V600E)-induced senescence was accompanied by simultaneous suppression of the PDH-inhibitory enzyme pyruvate dehydrogenase kinase 1 (PDK1) and induction of the PDH-activating enzyme pyruvate dehydrogenase phosphatase 2 (PDP2). The resulting combined activation of PDH enhanced the use of pyruvate in the tricarboxylic acid cycle, causing increased respiration and redox stress. Abrogation of OIS, a rate-limiting step towards oncogenic transformation, coincided with reversion of these processes. Further supporting a crucial role of PDH in OIS, enforced normalization of either PDK1 or PDP2 expression levels inhibited PDH and abrogated OIS, thereby licensing BRAF(V600E)-driven melanoma development. Finally, depletion of PDK1 eradicated melanoma subpopulations resistant to targeted BRAF inhibition, and caused regression of established melanomas. These results reveal a mechanistic relationship between OIS and a key metabolic signalling axis, which may be exploited therapeutically.

MIDcor, an R-program for deciphering mass interferences in mass spectra of metabolites enriched in stable isotopes.

BACKGROUND: Tracing stable isotopes, such as 13C using various mass spectrometry (MS) methods provides a valuable information necessary for the study of biochemical processes in cells. However, extracting such information requires special care, such as a correction for naturally occurring isotopes, or overlapping mass spectra of various components of the cell culture medium. Developing a method for a correction of overlapping peaks is the primary objective of this study. RESULTS: Our computer program-MIDcor (free at https://github.com/seliv55/mid_correct) written in the R programming language, corrects the raw MS spectra both for the naturally occurring isotopes and for the overlapping of peaks corresponding to various substances. To this end, the mass spectra of unlabeled metabolites measured in two media are necessary: in a minimal medium containing only derivatized metabolites and chemicals for derivatization, and in a complete cell incubated medium. The MIDcor program calculates the difference (D) between the theoretical and experimentally measured spectra of metabolites containing only the naturally occurring isotopes. The result of comparison of D in the two media determines a way of deciphering the true spectra. (1) If D in the complete medium is greater than that in the minimal medium in at least one peak, then unchanged D is subtracted from the raw spectra of the labeled metabolite. (2) If D does not depend on the medium, then the spectrum probably overlaps with a derivatized fragment of the same metabolite, and D is modified proportionally to the metabolite labeling. The program automatically reaches a decision regarding the way of correction. For some metabolites/fragments in the case (2) D was found to decrease when the tested substance was 13C labeled, and this isotopic effect also can be corrected automatically, if the user provides a measured spectrum of the substance in which the 13C labeling is known a priori. CONCLUSION: Using the developed program improves the reliability of stable isotope tracer data analysis.

Restrictions in ATP diffusion within sarcomeres can provoke ATP-depleted zones impairing exercise capacity in chronic obstructive pulmonary disease.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is characterized by the inability of patients to sustain a high level of ventilation resulting in perceived exertional discomfort and limited exercise capacity of leg muscles at average intracellular ATP levels sufficient to support contractility. METHODS: Myosin ATPase activity in biopsy samples from healthy and COPD individuals was implemented as a local nucleotide sensor to determine ATP diffusion coefficients within myofibrils. Ergometric parameters clinically measured during maximal exercise tests in both groups were used to define the rates of myosin ATPase reaction and aerobic ATP re-synthesis. The obtained parameters in combination with AK- and CK-catalyzed reactions were implemented to compute the kinetic and steady-state spatial ATP distributions within control and COPD sarcomeres. RESULTS: The developed reaction-diffusion model of two-dimensional sarcomeric space identified similar, yet extremely low nucleotide diffusion in normal and COPD myofibrils. The corresponding spatio-temporal ATP distributions, constructed during imposed exercise, predicted in COPD sarcomeres a depletion of ATP in the zones of overlap between actin and myosin filaments along the center axis at average cytosolic ATP levels similar to healthy muscles. CONCLUSIONS: ATP-depleted zones can induce rigor tension foci impairing muscle contraction and increase a risk for sarcomere damages. Thus, intra-sarcomeric diffusion restrictions at limited aerobic ATP re-synthesis can be an additional risk factor contributing to the muscle contractile deficiency experienced by COPD patients. GENERAL SIGNIFICANCE: This study demonstrates how restricted substrate mobility within a cellular organelle can provoke an energy imbalance state paradoxically occurring at abounding average metabolic resources.

Metabolic Reprogramming and Dependencies Associated with Epithelial Cancer Stem Cells Independent of the Epithelial-Mesenchymal Transition Program.

In solid tumors, cancer stem cells (CSCs) can arise independently of epithelial-mesenchymal transition (EMT). In spite of recent efforts, the metabolic reprogramming associated with CSC phenotypes uncoupled from EMT is poorly understood. Here, by using metabolomic and fluxomic approaches, we identify major metabolic profiles that differentiate metastatic prostate epithelial CSCs (e-CSCs) from non-CSCs expressing a stable EMT. We have found that the e-CSC program in our cellular model is characterized by a high plasticity in energy substrate metabolism, including an enhanced Warburg effect, a greater carbon and energy source flexibility driven by fatty acids and amino acid metabolism and an essential reliance on the proton buffering capacity conferred by glutamine metabolism. An analysis of transcriptomic data yielded a metabolic gene signature for our e-CSCs consistent with the metabolomics and fluxomics analyses that correlated with tumor progression and metastasis in prostate cancer and in 11 additional cancer types. Interestingly, an integrated metabolomics, fluxomics, and transcriptomics analysis allowed us to identify key metabolic players regulated at the post-transcriptional level, suggesting potential biomarkers and therapeutic targets to effectively forestall metastasis. Stem Cells 2016;34:1163-1176.

HepatoDyn: A Dynamic Model of Hepatocyte Metabolism That Integrates 13C Isotopomer Data.

The liver performs many essential metabolic functions, which can be studied using computational models of hepatocytes. Here we present HepatoDyn, a highly detailed dynamic model of hepatocyte metabolism. HepatoDyn includes a large metabolic network, highly detailed kinetic laws, and is capable of dynamically simulating the redox and energy metabolism of hepatocytes. Furthermore, the model was coupled to the module for isotopic label propagation of the software package IsoDyn, allowing HepatoDyn to integrate data derived from 13C based experiments. As an example of dynamical simulations applied to hepatocytes, we studied the effects of high fructose concentrations on hepatocyte metabolism by integrating data from experiments in which rat hepatocytes were incubated with 20 mM glucose supplemented with either 3 mM or 20 mM fructose. These experiments showed that glycogen accumulation was significantly lower in hepatocytes incubated with medium supplemented with 20 mM fructose than in hepatocytes incubated with medium supplemented with 3 mM fructose. Through the integration of extracellular fluxes and 13C enrichment measurements, HepatoDyn predicted that this phenomenon can be attributed to a depletion of cytosolic ATP and phosphate induced by high fructose concentrations in the medium.

Combined Analysis of NMR and MS Spectra (CANMS).

Cellular metabolism in mammalian cells represents a challenge for analytical chemistry in the context of current biomedical research. Mass spectrometry and NMR spectroscopy together with computational tools have been used to study metabolism in cells. Compartmentalization of metabolism complicates the interpretation of stable isotope patterns in mammalian cells owing to the superimposition of different pathways contributing to the same pool of analytes. This indicates a need for a model-free approach to interpret such data. Mass spectrometry and NMR spectroscopy provide complementary analytical information on metabolites. Herein an approach that simulates 13 C multiplets in NMR spectra and utilizes mass increments to obtain long-range information is presented. The combined information is then utilized to derive isotopomer distributions. This is a first rigorous analytical and computational approach for a model-free analysis of metabolic data applicable to mammalian cells.

Chronic Obstructive Pulmonary Disease heterogeneity: challenges for health risk assessment, stratification and management.

BACKGROUND AND HYPOTHESIS: Heterogeneity in clinical manifestations and disease progression in Chronic Obstructive Pulmonary Disease (COPD) lead to consequences for patient health risk assessment, stratification and management. Implicit with the classical "spill over" hypothesis is that COPD heterogeneity is driven by the pulmonary events of the disease. Alternatively, we hypothesized that COPD heterogeneities result from the interplay of mechanisms governing three conceptually different phenomena: 1) pulmonary disease, 2) systemic effects of COPD and 3) co-morbidity clustering, each of them with their own dynamics. OBJECTIVE AND METHOD: To explore the potential of a systems analysis of COPD heterogeneity focused on skeletal muscle dysfunction and on co-morbidity clustering aiming at generating predictive modeling with impact on patient management. To this end, strategies combining deterministic modeling and network medicine analyses of the Biobridge dataset were used to investigate the mechanisms of skeletal muscle dysfunction. An independent data driven analysis of co-morbidity clustering examining associated genes and pathways was performed using a large dataset (ICD9-CM data from Medicare, 13 million people). Finally, a targeted network analysis using the outcomes of the two approaches (skeletal muscle dysfunction and co-morbidity clustering) explored shared pathways between these phenomena. RESULTS: (1) Evidence of abnormal regulation of skeletal muscle bioenergetics and skeletal muscle remodeling showing a significant association with nitroso-redox disequilibrium was observed in COPD; (2) COPD patients presented higher risk for co-morbidity clustering than non-COPD patients increasing with ageing; and, (3) the on-going targeted network analyses suggests shared pathways between skeletal muscle dysfunction and co-morbidity clustering. CONCLUSIONS: The results indicate the high potential of a systems approach to address COPD heterogeneity. Significant knowledge gaps were identified that are relevant to shape strategies aiming at fostering 4P Medicine for patients with COPD.

Systems Medicine: from molecular features and models to the clinic in COPD.

BACKGROUND AND HYPOTHESIS: Chronic Obstructive Pulmonary Disease (COPD) patients are characterized by heterogeneous clinical manifestations and patterns of disease progression. Two major factors that can be used to identify COPD subtypes are muscle dysfunction/wasting and co-morbidity patterns. We hypothesized that COPD heterogeneity is in part the result of complex interactions between several genes and pathways. We explored the possibility of using a Systems Medicine approach to identify such pathways, as well as to generate predictive computational models that may be used in clinic practice. OBJECTIVE AND METHOD: Our overarching goal is to generate clinically applicable predictive models that characterize COPD heterogeneity through a Systems Medicine approach. To this end we have developed a general framework, consisting of three steps/objectives: (1) feature identification, (2) model generation and statistical validation, and (3) application and validation of the predictive models in the clinical scenario. We used muscle dysfunction and co-morbidity as test cases for this framework. RESULTS: In the study of muscle wasting we identified relevant features (genes) by a network analysis and generated predictive models that integrate mechanistic and probabilistic models. This allowed us to characterize muscle wasting as a general de-regulation of pathway interactions. In the co-morbidity analysis we identified relevant features (genes/pathways) by the integration of gene-disease and disease-disease associations. We further present a detailed characterization of co-morbidities in COPD patients that was implemented into a predictive model. In both use cases we were able to achieve predictive modeling but we also identified several key challenges, the most pressing being the validation and implementation into actual clinical practice. CONCLUSIONS: The results confirm the potential of the Systems Medicine approach to study complex diseases and generate clinically relevant predictive models. Our study also highlights important obstacles and bottlenecks for such approaches (e.g. data availability and normalization of frameworks among others) and suggests specific proposals to overcome them.

Relevance of the MEK/ERK signaling pathway in the metabolism of activated macrophages: a metabolomic approach.

The activation of immune cells in response to a pathogen involves a succession of signaling events leading to gene and protein expression, which requires metabolic changes to match the energy demands. The metabolic profile associated with the MAPK cascade (ERK1/2, p38, and JNK) in macrophages was studied, and the effect of its inhibition on the specific metabolic pattern of LPS stimulation was characterized. A [1,2-[(13)C](2)]glucose tracer-based metabolomic approach was used to examine the metabolic flux distribution in these cells after MEK/ERK inhibition. Bioinformatic tools were used to analyze changes in mass isotopomer distribution and changes in glucose and glutamine consumption and lactate production in basal and LPS-stimulated conditions in the presence and absence of the selective inhibitor of the MEK/ERK cascade, PD325901. Results showed that PD325901-mediated ERK1/2 inhibition significantly decreased glucose consumption and lactate production but did not affect glutamine consumption. These changes were accompanied by a decrease in the glycolytic flux, consistent with the observed decrease in fructose-2,6-bisphosphate concentration. The oxidative and nonoxidative pentose phosphate pathways and the ratio between them also decreased. However, tricarboxylic acid cycle flux did not change significantly. LPS activation led to the opposite responses, although all of these were suppressed by PD325901. However, LPS also induced a small decrease in pentose phosphate pathway fluxes and an increase in glutamine consumption that were not affected by PD325901. We concluded that inhibition of the MEK/ERK cascade interferes with central metabolism, and this cross-talk between signal transduction and metabolism also occurs in the presence of LPS.

Multistationary and oscillatory modes of free radicals generation by the mitochondrial respiratory chain revealed by a bifurcation analysis.

The mitochondrial electron transport chain transforms energy satisfying cellular demand and generates reactive oxygen species (ROS) that act as metabolic signals or destructive factors. Therefore, knowledge of the possible modes and bifurcations of electron transport that affect ROS signaling provides insight into the interrelationship of mitochondrial respiration with cellular metabolism. Here, a bifurcation analysis of a sequence of the electron transport chain models of increasing complexity was used to analyze the contribution of individual components to the modes of respiratory chain behavior. Our algorithm constructed models as large systems of ordinary differential equations describing the time evolution of the distribution of redox states of the respiratory complexes. The most complete model of the respiratory chain and linked metabolic reactions predicted that condensed mitochondria produce more ROS at low succinate concentration and less ROS at high succinate levels than swelled mitochondria. This prediction was validated by measuring ROS production under various swelling conditions. A numerical bifurcation analysis revealed qualitatively different types of multistationary behavior and sustained oscillations in the parameter space near a region that was previously found to describe the behavior of isolated mitochondria. The oscillations in transmembrane potential and ROS generation, observed in living cells were reproduced in the model that includes interaction of respiratory complexes with the reactions of TCA cycle. Whereas multistationarity is an internal characteristic of the respiratory chain, the functional link of respiration with central metabolism creates oscillations, which can be understood as a means of auto-regulation of cell metabolism.

Compartmentation of membrane processes and nucleotide dynamics in diffusion-restricted cardiac cell microenvironment.

Orchestrated excitation-contraction coupling in heart muscle requires adequate spatial arrangement of systems responsible for ion movement and metabolite turnover. Co-localization of regulatory and transporting proteins into macromolecular complexes within an environment of microanatomical cell components raises intracellular diffusion barriers that hamper the mobility of metabolites and signaling molecules. Compared to substrate diffusion in the cytosol, diffusional restrictions underneath the sarcolemma are much larger and could impede ion and nucleotide movement by a factor of 10(3)-10(5). Diffusion barriers thus seclude metabolites within the submembrane space enabling rapid and vectorial effector targeting, yet hinder energy supply from the bulk cytosolic space implicating the necessity for a shunting transfer mechanism. Here, we address principles of membrane protein compartmentation, phosphotransfer enzyme-facilitated interdomain energy transfer, and nucleotide signal dynamics at the subsarcolemma-cytosol interface. This article is part of a Special Issue entitled "Local Signaling in Myocytes".

Reactive oxygen species production by forward and reverse electron fluxes in the mitochondrial respiratory chain.

Reactive oxygen species (ROS) produced in the mitochondrial respiratory chain (RC) are primary signals that modulate cellular adaptation to environment, and are also destructive factors that damage cells under the conditions of hypoxia/reoxygenation relevant for various systemic diseases or transplantation. The important role of ROS in cell survival requires detailed investigation of mechanism and determinants of ROS production. To perform such an investigation we extended our rule-based model of complex III in order to account for electron transport in the whole RC coupled to proton translocation, transmembrane electrochemical potential generation, TCA cycle reactions, and substrate transport to mitochondria. It fits respiratory electron fluxes measured in rat brain mitochondria fueled by succinate or pyruvate and malate, and the dynamics of NAD(+) reduction by reverse electron transport from succinate through complex I. The fitting of measured characteristics gave an insight into the mechanism of underlying processes governing the formation of free radicals that can transfer an unpaired electron to oxygen-producing superoxide and thus can initiate the generation of ROS. Our analysis revealed an association of ROS production with levels of specific radicals of individual electron transporters and their combinations in species of complexes I and III. It was found that the phenomenon of bistability, revealed previously as a property of complex III, remains valid for the whole RC. The conditions for switching to a state with a high content of free radicals in complex III were predicted based on theoretical analysis and were confirmed experimentally. These findings provide a new insight into the mechanisms of ROS production in RC.

MITODYN: An Open Source Software for Quantitative Modeling of Mitochondrial and Cellular Energy Metabolic Flux Dynamics in Health and Disease.

Mitochondrial respiratory chain (RC) transforms the reductive power of NADH or FADH2 oxidation into a proton gradient between the matrix and cytosolic sides of the inner mitochondrial membrane, that ATP synthase uses to generate ATP. This process constitutes a bridge between carbohydrates' central metabolism and ATP-consuming cellular functions. Moreover, the RC is responsible for a large part of reactive oxygen species (ROS) generation that play signaling and oxidizing roles in cells. Mathematical methods and computational analysis are required to understand and predict the possible behavior of this metabolic system. Here we propose a software tool that helps to analyze individual steps of respiratory electron transport in their dynamics, thus deepening understanding of the mechanism of energy transformation and ROS generation in the RC. This software's core is a kinetic model of the RC represented by a system of ordinary differential equations (ODEs). This model enables the analysis of complex dynamic behavior of the RC, including multistationarity and oscillations. The proposed RC modeling method can be applied to study respiration and ROS generation in various organisms and naturally extended to explore carbohydrates' metabolism and linked metabolic processes.

Unveiling a key role of oxaloacetate-glutamate interaction in regulation of respiration and ROS generation in nonsynaptic brain mitochondria using a kinetic model.

Glutamate plays diverse roles in neuronal cells, affecting cell energetics and reactive oxygen species (ROS) generation. These roles are especially vital for neuronal cells, which deal with high amounts of glutamate as a neurotransmitter. Our analysis explored neuronal glutamate implication in cellular energy metabolism and ROS generation, using a kinetic model that simulates electron transport details in respiratory complexes, linked ROS generation and metabolic reactions. The analysis focused on the fact that glutamate attenuates complex II inhibition by oxaloacetate, stimulating the latter's transformation into aspartate. Such a mechanism of complex II activation by glutamate could cause almost complete reduction of ubiquinone and deficiency of oxidized form (Q), which closes the main stream of electron transport and opens a way to massive ROS generating transfer in complex III from semiquinone radicals to molecular oxygen. In this way, under low workload, glutamate triggers the respiratory chain (RC) into a different steady state characterized by high ROS generation rate. The observed stepwise dependence of ROS generation on glutamate concentration experimentally validated this prediction. However, glutamate's attenuation of oxaloacetate's inhibition accelerates electron transport under high workload. Glutamate-oxaloacetate interaction in complex II regulation underlies the observed effects of uncouplers and inhibitors and acceleration of Ca2+ uptake. Thus, this theoretical analysis uncovered the previously unknown roles of oxaloacetate as a regulator of ROS generation and glutamate as a modifier of this regulation. The model predicted that this mechanism of complex II activation by glutamate might be operative in situ and responsible for excitotoxicity. Spatial-time gradients of synthesized hydrogen peroxide concentration, calculated in the reaction-diffusion model with convection under a non-uniform local approximation of nervous tissue, have shown that overproduction of H2O2 in a cell causes excess of its level in neighbor cells.

Bistability of mitochondrial respiration underlies paradoxical reactive oxygen species generation induced by anoxia.

Increased production of reactive oxygen species (ROS) in mitochondria underlies major systemic diseases, and this clinical problem stimulates a great scientific interest in the mechanism of ROS generation. However, the mechanism of hypoxia-induced change in ROS production is not fully understood. To mathematically analyze this mechanism in details, taking into consideration all the possible redox states formed in the process of electron transport, even for respiratory complex III, a system of hundreds of differential equations must be constructed. Aimed to facilitate such tasks, we developed a new methodology of modeling, which resides in the automated construction of large sets of differential equations. The detailed modeling of electron transport in mitochondria allowed for the identification of two steady state modes of operation (bistability) of respiratory complex III at the same microenvironmental conditions. Various perturbations could induce the transition of respiratory chain from one steady state to another. While normally complex III is in a low ROS producing mode, temporal anoxia could switch it to a high ROS producing state, which persists after the return to normal oxygen supply. This prediction, which we qualitatively validated experimentally, explains the mechanism of anoxia-induced cell damage. Recognition of bistability of complex III operation may enable novel therapeutic strategies for oxidative stress and our method of modeling could be widely used in systems biology studies.

Software Supporting a Workflow of Quantitative Dynamic Flux Maps Estimation in Central Metabolism from SIRM Experimental Data.

Stable isotope-resolved metabolomics (SIRM), based on the analysis of biological samples from living cells incubated with artificial isotope enriched substrates, enables mapping the rates of biochemical reactions (metabolic fluxes). We developed software supporting a workflow of analysis of SIRM data obtained with mass spectrometry (MS). The evaluation of fluxes starting from raw MS recordings requires at least three steps of computer support: first, extraction of mass spectra of metabolites of interest, then correction of the spectra for natural isotope abundance, and finally, evaluation of fluxes by simulation of the corrected spectra using a corresponding mathematical model. A kinetic model based on ordinary differential equations (ODEs) for isotopomers of metabolites of the corresponding biochemical network supports the final part of the analysis, which provides a dynamic flux map.

Half-of-the-sites reactivity of transketolase from Saccharomyces cerevisiae.

Cleavage by yeast transketolase of the donor substrate, D-xylulose 5-phosphate, in the absence of the acceptor substrate was studied using stopped-flow spectrophotometry. One mole of the substrate was shown to be cleaved in the prestationary phase, leading to the formation of one mole of the reaction product per mole enzyme, which has two active centers. This observation indicates that only one out of the two active centers functions (i.e., binds and cleaves the substrate) at a time. Such half-of-the-sites reactivity of transketolase conforms well with our understanding, proposed previously, that the active centers of the enzyme operate in sequence (in phase opposition): the cleavage of a ketose within one center (first phase of the transketolase reaction) is paralleled by its formation in the other center (glycolaldehyde residue is condensed with the acceptor substrate, and the second stage of the transketolase reaction is thereby completed) [M.V. Kovina, G.A. Kochetov, FEBS Lett. 440 (1998) 81-84].

The landscape of tiered regulation of breast cancer cell metabolism.

Altered metabolism is a hallmark of cancer, but little is still known about its regulation. In this study, we measure transcriptomic, proteomic, phospho-proteomic and fluxomics data in a breast cancer cell-line (MCF7) across three different growth conditions. Integrating these multiomics data within a genome scale human metabolic model in combination with machine learning, we systematically chart the different layers of metabolic regulation in breast cancer cells, predicting which enzymes and pathways are regulated at which level. We distinguish between two types of reactions, directly and indirectly regulated. Directly-regulated reactions include those whose flux is regulated by transcriptomic alterations (~890) or via proteomic or phospho-proteomics alterations (~140) in the enzymes catalyzing them. We term the reactions that currently lack evidence for direct regulation as (putative) indirectly regulated (~930). Many metabolic pathways are predicted to be regulated at different levels, and those may change at different media conditions. Remarkably, we find that the flux of predicted indirectly regulated reactions is strongly coupled to the flux of the predicted directly regulated ones, uncovering a tiered hierarchical organization of breast cancer cell metabolism. Furthermore, the predicted indirectly regulated reactions are predominantly reversible. Taken together, this architecture may facilitate rapid and efficient metabolic reprogramming in response to the varying environmental conditions incurred by the tumor cells. The approach presented lays a conceptual and computational basis for mapping metabolic regulation in additional cancers.