Metabolic flux analysis and fluxomics-driven determination of reaction free energy using multiple isotopes

The marriage between stable isotope ecology and plant metabolomics - new perspectives for metabolic flux analysis and the interpretation of ecological archives

Even though they share many thematical overlaps, plant metabolomics and stable isotope ecology have been rather separate fields mainly due to different mass spectrometry demands. New high-resolution bioanalytical mass spectrometers are now not only offering high-throughput metabolite identification but are also suitable for compound- and intramolecular position-specific isotope analysis in the natural isotope abundance range. In plant metabolomics, label-free metabolic pathway and metabolic flux analysis might become possible when applying this new technology. This is because changes in the commitment of substrates to particular metabolic pathways and the activation or deactivation of others alter enzyme-specific isotope effects. This leads to differences in intramolecular and compound-specific isotope compositions. In plant isotope ecology, position-specific isotope analysis in plant archives informed by metabolic pathway analysis could be used to reconstruct and separate environmental impacts on complex metabolic processes. A technology-driven linkage between the two disciplines could allow to extract information on environment-metabolism interaction from plant archives such as tree rings but also within ecosystems. This would contribute to a holistic understanding of how plants react to environmental drivers, thus also providing helpful information on the trajectories of the vegetation under the conditions to come.

Rethinking 13C-metabolic flux analysis - The Bayesian way of flux inference

Metabolic reaction rates (fluxes) play a crucial role in comprehending cellular phenotypes and are essential in areas such as metabolic engineering, biotechnology, and biomedical research. The state-of-the-art technique for estimating fluxes is metabolic flux analysis using isotopic labelling (13C-MFA), which uses a dataset-model combination to determine the fluxes. Bayesian statistical methods are gaining popularity in the field of life sciences, but the use of 13C-MFA is still dominated by conventional best-fit approaches. The slow take-up of Bayesian approaches is, at least partly, due to the unfamiliarity of Bayesian methods to metabolic engineering researchers. To address this unfamiliarity, we here outline similarities and differences between the two approaches and highlight particular advantages of the Bayesian way of flux analysis. With a real-life example, re-analysing a moderately informative labelling dataset of E. coli, we identify situations in which Bayesian methods are advantageous and more informative, pointing to potential pitfalls of current 13C-MFA evaluation approaches. We propose the use of Bayesian model averaging (BMA) for flux inference as a means of overcoming the problem of model uncertainty through its tendency to assign low probabilities to both, models that are unsupported by data, and models that are overly complex. In this capacity, BMA resembles a tempered Ockham's razor. With the tempered razor as a guide, BMA-based 13C-MFA alleviates the problem of model selection uncertainty and is thereby capable of becoming a game changer for metabolic engineering by uncovering new insights and inspiring novel approaches.

Kinetic modelling of the cellular metabolic responses underpinning in vitro glycolysis assays

This study aims to demonstrate the benefits of augmenting commercially available, real-time, in vitro glycolysis assays with phenomenological rate equation-based kinetic models, describing the contributions of the underpinning metabolic pathways. To this end, a commercially available glycolysis assay, sensitive to changes in extracellular acidification (extracellular pH), was used to derive the glycolysis pathway kinetics. The pathway was numerically modelled using a series of ordinary differential rate equations, to simulate the obtained experimental results. The sensitivity of the model to the key equation parameters was also explored. The cellular glycolysis pathway kinetics were determined for three different cell-lines, under nonmodulated and modulated conditions. Over the timescale studied, the assay demonstrated a two-phase metabolic response, representing the differential kinetics of glycolysis pathway rate as a function of time, and this behaviour was faithfully reproduced by the model simulations. The model enabled quantitative comparison of the pathway kinetics of three cell lines, and also the modulating effect of two known drugs. Moreover, the modelling tool allows the subtle differences between different cell lines to be better elucidated and also allows augmentation of the assay sensitivity. A simplistic numerical model can faithfully reproduce the differential pathway kinetics for three different cell lines, with and without pathway-modulating drugs, and furthermore provides insights into the cellular metabolism by elucidating the underlying mechanisms leading to the pathway end-product. This study demonstrates that augmenting a relatively simple, real-time, in vitro assay with a model of the underpinning metabolic pathway provides considerable insights into the observed differences in cellular systems.

Fluorescence-activated multi-organelle mapping of subcellular plant hormone distribution

Auxins and cytokinins are two major families of phytohormones that control most aspects of plant growth, development and plasticity. Their distribution in plants has been described, but the importance of cell- and subcellular-type specific phytohormone homeostasis remains undefined. Herein, we revealed auxin and cytokinin distribution maps showing their different organelle-specific allocations within the Arabidopsis plant cell. To do so, we have developed Fluorescence-Activated multi-Organelle Sorting (FAmOS), an innovative subcellular fractionation technique based on flow cytometric principles. FAmOS allows the simultaneous sorting of four differently labelled organelles based on their individual light scatter and fluorescence parameters while ensuring hormone metabolic stability. Our data showed different subcellular distribution of auxin and cytokinins, revealing the formation of phytohormone gradients that have been suggested by the subcellular localization of auxin and cytokinin transporters, receptors and metabolic enzymes. Both hormones showed enrichment in vacuoles, while cytokinins were also accumulated in the endoplasmic reticulum.

Deuterated water as a substrate-agnostic isotope tracer for investigating reversibility and thermodynamics of reactions in central carbon metabolism

Stable isotope tracers are a powerful tool for the quantitative analysis of microbial metabolism, enabling pathway elucidation, metabolic flux quantification, and assessment of reaction and pathway thermodynamics. 13C and 2H metabolic flux analysis commonly relies on isotopically labeled carbon substrates, such as glucose. However, the use of 2H-labeled nutrient substrates faces limitations due to their high cost and limited availability in comparison to 13C-tracers. Furthermore, isotope tracer studies in industrially relevant bacteria that metabolize complex substrates such as cellulose, hemicellulose, or lignocellulosic biomass, are challenging given the difficulty in obtaining these as isotopically labeled substrates. In this study, we examine the potential of deuterated water (2H2O) as an affordable, substrate-neutral isotope tracer for studying central carbon metabolism. We apply 2H2O labeling to investigate the reversibility of glycolytic reactions across three industrially relevant bacterial species -C. thermocellum, Z. mobilis, and E. coli-harboring distinct glycolytic pathways with unique thermodynamics. We demonstrate that 2H2O labeling recapitulates previous reversibility and thermodynamic findings obtained with established 13C and 2H labeled nutrient substrates. Furthermore, we exemplify the utility of this 2H2O labeling approach by applying it to high-substrate C. thermocellum fermentations -a setting in which the use of conventional tracers is impractical-thereby identifying the glycolytic enzyme phosphofructokinase as a major bottleneck during high-substrate fermentations and unveiling critical insights that will steer future engineering efforts to enhance ethanol production in this cellulolytic organism. This study demonstrates the utility of deuterated water as a substrate-agnostic isotope tracer for examining flux and reversibility of central carbon metabolic reactions, which yields biological insights comparable to those obtained using costly 2H-labeled nutrient substrates.

Advancing CAR T cell therapy through the use of multidimensional omics data

Despite the notable success of chimeric antigen receptor (CAR) T cell therapies in the treatment of certain haematological malignancies, challenges remain in optimizing CAR designs and cell products, improving response rates, extending the durability of remissions, reducing toxicity and broadening the utility of this therapeutic modality to other cancer types. Data from multidimensional omics analyses, including genomics, epigenomics, transcriptomics, T cell receptor-repertoire profiling, proteomics, metabolomics and/or microbiomics, provide unique opportunities to dissect the complex and dynamic multifactorial phenotypes, processes and responses of CAR T cells as well as to discover novel tumour targets and pathways of resistance. In this Review, we summarize the multidimensional cellular and molecular profiling technologies that have been used to advance our mechanistic understanding of CAR T cell therapies. In addition, we discuss current applications and potential strategies leveraging multi-omics data to identify optimal target antigens and other molecular features that could be exploited to enhance the antitumour activity and minimize the toxicity of CAR T cell therapy. Indeed, fully utilizing multi-omics data will provide new insights into the biology of CAR T cell therapy, further accelerate the development of products with improved efficacy and safety profiles, and enable clinicians to better predict and monitor patient responses.

Novel targets for ameliorating energy metabolism disorders in depression through stable isotope-resolved metabolomics

The severe harm of depression to human health and life has attracted global attention, but the exact mechanism is not yet known due to the complicated pathogenesis. The existing antidepressants are far from ideal, indicating it is urgently needed to seek safe and effective drugs from a unique perspective. Based on the hypothesis of "mitochondrial dysfunction" proposed recently, we attempt to focus on the substrates supply of energy metabolism. We applied stable isotope-resolved metabolomics, and revealed that significantly decreased TCA cycle and abnormally increased gluconeogenesis pathway in CUMS rats. Pyruvate dehydrogenase (PDH) and pyruvate carboxylase (PC) maybe the key metabolic enzymes. This metabolic reprogramming was confirmed through ELISA assays and Western blot analysis. To explore the causes of substrates supply disorder in depression, we conducted the mitochondrial structure-function evaluation. Interestingly, the levels of the mitochondrial pyruvate carrier (MPC) decreased significantly, which is essential for the entry of pyruvic acid into the TCA cycle. Together, MPC, PDH and PC are expected to become potential novel therapeutic targets for treating depressive disorders. This research provides a unique insight for re-cognizing the pathological mechanisms of depression, the novel targets for development of ideal antidepressants, as well as a paradigm for deciphering abnormal metabolic pathways in other metabolic diseases.

Reduced Nucleotides, Thiols and O2 in Cellular Redox Balance: A Biochemist's View

In the present review, which is aimed at researchers, teachers and students in life sciences, we try to show how the physicochemical properties of the elements and molecules define the concept of redox balance. Living organism are open systems traversed by fluxes of energy and matter. During catabolic oxidative metabolism, matter-mostly hydrogenated organic molecules-is oxidized and ultimately released as CO₂. Electrons are passed over to coupling molecules, such as NAD+ and FAD, whose reduced forms serve as electrons donors in anabolic reactions. Early photosynthetic activity led to the accumulation of O₂ and the transformation of the reduction to an oxidizing atmosphere, favoring the development of oxidative metabolism in living organisms. We focus on the specific properties of O₂ that provide the chemical energy for the combustion reactions occurring in living cells. We explain the concepts of redox potential and redox balance in complex systems such as living cells, we present the main redox couples involved in cellular redox balance and we discuss the chemical properties underlying their cellular roles and, in particular, their antioxidant properties in the defense against reactive oxygen species (ROS). Finally, we try to provide an integrative view emphasizing the interplay between metabolism, oxidative stress and metabolic compartmentation in mammalian cells.

Tracing metabolic flux in vivo: basic model structures of tracer methodology

Molecules in living organisms are in a constant state of turnover at varying rates, i.e., synthesis, breakdown, oxidation, and/or conversion to different compounds. Despite the dynamic nature of biomolecules, metabolic research has focused heavily on static, snapshot information such as the abundances of mRNA, protein, and metabolites and/or (in)activation of molecular signaling, often leading to erroneous conclusions regarding metabolic status. Over the past century, stable, non-radioactive isotope tracers have been widely used to provide critical information on the dynamics of specific biomolecules (metabolites and polymers including lipids, proteins, and DNA), in studies in vitro in cells as well as in vivo in both animals and humans. In this review, we discuss (1) the historical background of the use of stable isotope tracer methodology in metabolic research; (2) the importance of obtaining kinetic information for a better understanding of metabolism; and (3) the basic principles and model structures of stable isotope tracer methodology using ¹³C-, ¹⁵N-, or ²H-labeled tracers.

Tagging biomolecules with stable isotopes of specific atoms can reveal details of the molecular inter-conversions of metabolism. The masses of the tracer isotopes used are greater than those of the more common atomic forms. This allows their movement through different metabolic pathways to be detected using mass spectrometry and modeling. Il-Young Kim at Gachon University School of Medicine in South Korea and colleagues focus their review on the use of stable, non-radioactive isotope tracers, especially, of carbon, nitrogen, and hydrogen, to study metabolism in live humans and other animals. They cover the basic model structures of tracer methodology that serve as the fundamental basis for various tracer methods available and the most recent applications. Their procedure is especially useful for monitoring the rates of metabolic inter-conversions, which can reveal aspects of health and disease.

Adapting isotopic tracer and metabolic flux analysis approaches to study C1 metabolism

Single-carbon (C1, or one-carbon) substrates are promising feedstocks for sustainable biofuel and biochemical production. Crucial to the goal of engineering C1-utilizing strains for improved production is a quantitative understanding of the organization, regulation and rates of the reactions that underpin C1 metabolism. ¹³C Metabolic flux analysis (MFA) is a well-established platform for interrogating these questions with multi-carbon substrates, and uses the differential labeling of metabolites that results from feeding a substrate with position-specific incorporation of ¹³C in order to infer quantitative fluxes and pathway topology. Adapting isotopic tracer approaches to C1 metabolism, where position-specific substrate labeling is impossible, requires additional experimental considerations. Here we review recent studies that have developed isotopic tracer approaches to overcome the challenge of uniform metabolite labeling and provide quantitative insight into C1 metabolism.

Metabolic Remodeling during Nitrogen Fixation in Zymomonas mobilis

Zymomonas mobilis is an ethanologenic bacterium currently being developed for production of advanced biofuels. Recent studies have shown that Z. mobilis can fix dinitrogen gas (N2) as a sole nitrogen source. During N2 fixation, Z. mobilis exhibits increased biomass-specific rates of ethanol production. In order to better understand the physiology of Z. mobilis during N2 fixation and during changes in ammonium (NH4+) availability, we performed liquid chromatography-mass spectrometry (LC-MS)-based targeted metabolomics and shotgun proteomics under three regimes of nitrogen availability: continuous N2 fixation, gradual NH4+ depletion, and acute NH4+ addition to N2-fixing cells. We report dynamic changes in abundance of proteins and metabolites related to nitrogen fixation, motility, ammonium assimilation, amino acid biosynthesis, nucleotide biosynthesis, isoprenoid biosynthesis, and Entner-Doudoroff (ED) glycolysis, providing insight into the regulatory mechanisms that control these processes in Z. mobilis. Our analysis identified potential physiological mechanisms that may contribute to increased specific ethanol production during N2 fixation, including decreased activity of biosynthetic pathways, increased protein abundance of alcohol dehydrogenase (ADHI), and increased thermodynamic favorability of the ED pathway. Of particular relevance to advanced biofuel production, we found that intermediates in the methylerythritol phosphate (MEP) pathway for isoprenoid biosynthesis were depleted during N2 fixation, coinciding with decreased protein abundance of deoxyxylulose 5-phosphate synthase (DXS), the first enzyme in the pathway. This implies that DXS protein abundance serves as a native control point in regulating MEP pathway activity in Z. mobilis. The results of this study will inform metabolic engineering to further develop Z. mobilis as a platform organism for biofuel production. IMPORTANCE Biofuels and bioproducts have the potential to serve as environmentally sustainable replacements for petroleum-derived fuels and commodity molecules. Advanced fuels such as higher alcohols and isoprenoids are more suitable gasoline replacements than bioethanol. Developing microbial systems to generate advanced biofuels requires metabolic engineering to reroute carbon away from ethanol and other native products and toward desired pathways, such as the MEP pathway for isoprenoid biosynthesis. However, rational engineering of microbial metabolism relies on understanding metabolic control points, in terms of both enzyme activity and thermodynamic favorability. In Z. mobilis, the factors that control glycolytic rates, ethanol production, and isoprenoid production are still not fully understood. In this study, we performed metabolomic, proteomic, and thermodynamic analysis of Z. mobilis during N2 fixation. This analysis identified key changes in metabolite levels, enzyme abundance, and glycolytic thermodynamic favorability that occurred during changes in NH4+ availability, helping to inform future efforts in metabolic engineering.

Cardiac Metabolism and Contractile Function in Mice with Reduced Trans-Endothelial Fatty Acid Transport

The heart is a metabolic omnivore that combusts a considerable amount of energy substrates, mainly long-chain fatty acids (FAs) and others such as glucose, lactate, ketone bodies, and amino acids. There is emerging evidence that muscle-type continuous capillaries comprise the rate-limiting barrier that regulates FA uptake into cardiomyocytes. The transport of FAs across the capillary endothelium is composed of three major steps-the lipolysis of triglyceride on the luminal side of the endothelium, FA uptake by the plasma membrane, and intracellular FA transport by cytosolic proteins. In the heart, impaired trans-endothelial FA (TEFA) transport causes reduced FA uptake, with a compensatory increase in glucose use. In most cases, mice with reduced FA uptake exhibit preserved cardiac function under unstressed conditions. When the workload is increased, however, the total energy supply relative to its demand (estimated with pool size in the tricarboxylic acid (TCA) cycle) is significantly diminished, resulting in contractile dysfunction. The supplementation of alternative fuels, such as medium-chain FAs and ketone bodies, at least partially restores contractile dysfunction, indicating that energy insufficiency due to reduced FA supply is the predominant cause of cardiac dysfunction. Based on recent in vivo findings, this review provides the following information related to TEFA transport: (1) the mechanisms of FA uptake by the heart, including TEFA transport; (2) the molecular mechanisms underlying the induction of genes associated with TEFA transport; (3) in vivo cardiac metabolism and contractile function in mice with reduced TEFA transport under unstressed conditions; and (4) in vivo contractile dysfunction in mice with reduced TEFA transport under diseased conditions, including an increased afterload and streptozotocin-induced diabetes.

AccuCor2: isotope natural abundance correction for dual-isotope tracer experiments

Stable isotope labeling techniques have been widely applied in the field of metabolomics and proteomics. Before the measured mass spectral data can be used for quantitative analysis, it must be accurately corrected for isotope natural abundance and tracer isotopic impurity. Despite the increasing popularity of dual-isotope tracing strategy such as 13C-15N or 13C-2H, there are no accurate tools for correcting isotope natural abundance for such experiments in a resolution-dependent manner. Here, we present AccuCor2 as an R-based tool to perform the correction for 13C-15N or 13C-2H labeling experiments. Our method uses a newly designed algorithm to construct the correction matrices that link labeling pattern and measured mass fractions, then use non-negative least-squares to solve the labeling patterns. Our results show that the dual-isotope experiments often require a mass resolution that is high enough to resolve 13C and 15N or 13C and 2H. Otherwise, the labeling pattern is not solvable. However, this mass resolution may not be sufficiently high to resolve other non-tracer elements such as oxygen or sulfur from the tracer elements. Therefore, we design AccuCor2 to perform the correction based on the actual mass resolution of the measurements. Using both simulated and experimental data, we show that AccuCor2 performs accurate and resolution-dependent correction for dual-isotope tracer data.

dGPredictor: Automated fragmentation method for metabolic reaction free energy prediction and de novo pathway design

Group contribution (GC) methods are conventionally used in thermodynamics analysis of metabolic pathways to estimate the standard Gibbs energy change (Δ_rG′^o) of enzymatic reactions from limited experimental measurements. However, these methods are limited by their dependence on manually curated groups and inability to capture stereochemical information, leading to low reaction coverage. Herein, we introduce an automated molecular fingerprint-based thermodynamic analysis tool called dGPredictor that enables the consideration of stereochemistry within metabolite structures and thus increases reaction coverage. dGPredictor has comparable prediction accuracy compared to existing GC methods and can capture Gibbs energy changes for isomerase and transferase reactions, which exhibit no overall group changes. We also demonstrate dGPredictor’s ability to predict the Gibbs energy change for novel reactions and seamless integration within de novo metabolic pathway design tools such as novoStoic for safeguarding against the inclusion of reaction steps with infeasible directionalities. To facilitate easy access to dGPredictor, we developed a graphical user interface to predict the standard Gibbs energy change for reactions at various pH and ionic strengths. The tool allows customized user input of known metabolites as KEGG IDs and novel metabolites as InChI strings (https://github.com/maranasgroup/dGPredictor).

The standard Gibbs energy change is commonly used to check for the feasibility of enzyme-catalyzed reactions as thermodynamics plays a crucial role in pathway design for biochemical synthesis. The group contribution methods using expert-defined functional groups have been extensively used for estimating standard Gibbs energy change. Here, we introduce a molecular fingerprint-based thermodynamic tool, dGPredictor, that enables distinguishing between (stereo)isomers in metabolic reactions leading to improved reaction coverage and comparable prediction accuracy as GC methods. dGPredictor can also be used alongside de novo pathway design tools to ensure the correct directionality of chosen reaction steps. We applied and tested dGPredictor on reactions from the KEGG database and applied it to screen an isobutanol synthesis pathway design. An open-source, user-friendly web interface is provided to facilitate easy access for standard Gibbs energy change of reactions at different pH values. (https://github.com/maranasgroup/dGPredictor).

Hostile Takeover: How Viruses Reprogram Prokaryotic Metabolism

To reproduce, prokaryotic viruses must hijack the cellular machinery of their hosts and redirect it toward the production of viral particles. While takeover of the host replication and protein synthesis apparatus has long been considered an essential feature of infection, recent studies indicate that extensive reprogramming of host primary metabolism is a widespread phenomenon among prokaryotic viruses that is required to fulfill the biosynthetic needs of virion production. In this review we provide an overview of the most significant recent findings regarding virus-induced reprogramming of prokaryotic metabolism and suggest how quantitative systems biology approaches may be used to provide a holistic understanding of metabolic remodeling during lytic viral infection. Expected final online publication date for the Annual Review of Microbiology, Volume 75 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Metabolomics and Lipidomics: Expanding the Molecular Landscape of Exercise Biology

Dynamic changes in circulating and tissue metabolites and lipids occur in response to exercise-induced cellular and whole-body energy demands to maintain metabolic homeostasis. The metabolome and lipidome in a given biological system provides a molecular snapshot of these rapid and complex metabolic perturbations. The application of metabolomics and lipidomics to map the metabolic responses to an acute bout of aerobic/endurance or resistance exercise has dramatically expanded over the past decade thanks to major analytical advancements, with most exercise-related studies to date focused on analyzing human biofluids and tissues. Experimental and analytical considerations, as well as complementary studies using animal model systems, are warranted to help overcome challenges associated with large human interindividual variability and decipher the breadth of molecular mechanisms underlying the metabolic health-promoting effects of exercise. In this review, we provide a guide for exercise researchers regarding analytical techniques and experimental workflows commonly used in metabolomics and lipidomics. Furthermore, we discuss advancements in human and mammalian exercise research utilizing metabolomic and lipidomic approaches in the last decade, as well as highlight key technical considerations and remaining knowledge gaps to continue expanding the molecular landscape of exercise biology.

A guide to metabolic flux analysis in metabolic engineering: Methods, tools and applications

The field of metabolic engineering is primarily concerned with improving the biological production of value-added chemicals, fuels and pharmaceuticals through the design, construction and optimization of metabolic pathways, redirection of intracellular fluxes, and refinement of cellular properties relevant for industrial bioprocess implementation. Metabolic network models and metabolic fluxes are central concepts in metabolic engineering, as was emphasized in the first paper published in this journal, "Metabolic fluxes and metabolic engineering" (Metabolic Engineering, 1: 1-11, 1999). In the past two decades, a wide range of computational, analytical and experimental approaches have been developed to interrogate the capabilities of biological systems through analysis of metabolic network models using techniques such as flux balance analysis (FBA), and quantify metabolic fluxes using constrained-based modeling approaches such as metabolic flux analysis (MFA) and more advanced experimental techniques based on the use of stable-isotope tracers, i.e. ¹³C-metabolic flux analysis (¹³C-MFA). In this review, we describe the basic principles of metabolic flux analysis, discuss current best practices in flux quantification, highlight potential pitfalls and alternative approaches in the application of these tools, and give a broad overview of pragmatic applications of flux analysis in metabolic engineering practice.