How metabolites modulate metabolic flux

Genome-wide transcriptome profiling of transgenic hop (Humulus lupulus L.) constitutively overexpressing HlWRKY1 and HlWDR1 transcription factors

Background

The hop plant (Humulus lupulus L.) is a valuable source of several secondary metabolites, such as flavonoids, bitter acids, and essential oils. These compounds are widely implicated in the beer brewing industry and are having potential biomedical applications. Several independent breeding programs around the world have been initiated to develop new cultivars with enriched lupulin and secondary metabolite contents but met with limited success due to several constraints. In the present work, a pioneering attempt has been made to overexpress master regulator binary transcription factor complex formed by HlWRKY1 and HlWDR1 using a plant expression vector to enhance the level of prenylflavonoid and bitter acid content in the hop. Subsequently, we performed transcriptional profiling using high-throughput RNA-Seq technology in leaves of resultant transformants and wild-type hop to gain in-depth information about the genome-wide functional changes induced by HlWRKY1 and HlWDR1 overexpression.

Results

The transgenic WW-lines exhibited an elevated expression of structural and regulatory genes involved in prenylflavonoid and bitter acid biosynthesis pathways. In addition, the comparative transcriptome analysis revealed a total of 522 transcripts involved in 30 pathways, including lipids and amino acids biosynthesis, primary carbon metabolism, phytohormone signaling and stress responses were differentially expressed in WW-transformants. It was apparent from the whole transcriptome sequencing that modulation of primary carbon metabolism and other pathways by HlWRKY1 and HlWDR1 overexpression resulted in enhanced substrate flux towards secondary metabolites pathway. The detailed analyses suggested that none of the pathways or genes, which have a detrimental effect on physiology, growth and development processes, were induced on a genome-wide scale in WW-transgenic lines.

Conclusions

Taken together, our results suggest that HlWRKY1 and HlWDR1 simultaneous overexpression positively regulates the prenylflavonoid and bitter acid biosynthesis pathways in the hop and thus these transgenes are presented as prospective candidates for achieving enhanced secondary metabolite content in the hop.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5125-8) contains supplementary material, which is available to authorized users.

Non-transcriptional processes in circadian rhythm generation

'Biological clocks' orchestrate mammalian biology to a daily rhythm. Whilst 'clock gene' transcriptional circuits impart rhythmic regulation to myriad cellular systems, our picture of the biochemical mechanisms that determine their circadian (∼24 hour) period is incomplete. Here we consider the evidence supporting different models for circadian rhythm generation in mammalian cells in light of evolutionary factors. We find it plausible that the circadian timekeeping mechanism in mammalian cells is primarily protein-based, signalling biological timing information to the nucleus by the post-translational regulation of transcription factor activity, with transcriptional feedback imparting robustness to the oscillation via hysteresis. We conclude by suggesting experiments that might distinguish this model from competing paradigms.

Ex Vivo Enteroids Recapitulate In Vivo Citrulline Production in Mice

Background

The endogenous production of arginine relies on the synthesis of citrulline by enteral ornithine transcarbamylase (OTC). Mutations in the gene coding for this enzyme are the most frequent cause of urea cycle disorders. There is a lack of correlation between in vivo metabolic function and DNA sequence, transcript abundance, or in vitro enzyme activity.

Objective

The goal of the present work was to test the hypothesis that enteroids, a novel ex vivo model, are able to recapitulate the in vivo citrulline production of wild-type (WT) and mutant mice.

Methods

Six-week-old male WT and OTC-deficient mice [sparse fur and abnormal skin (spf-ash) mutation] were studied. Urea and citrulline fluxes were determined in vivo, and OTC abundance was measured in liver and gut tissue. Intestinal crypts were isolated and cultured to develop enteroids. Ex vivo citrulline production and OTC abundance were determined in these enteroids.

Results

Liver OTC abundance was lower (mean ± SE: 0.16 ± 0.01 compared with 1.85 ± 0.18 arbitrary units; P < 0.001) in spf-ash mice than in WT mice, but there was no difference in urea production. In gut tissue, OTC was barely detectable in mutant mice; despite this, a lower but substantial citrulline production (67 ± 3 compared with 167 ± 8 µmol · kg-1 · h-1; P < 0.001) was shown in the mutant mice. Enteroids recapitulated the in vivo findings of a very low OTC content accompanied by a reduced citrulline production (1.07 ± 0.20 compared with 4.64 ± 0.44 nmol · µg DNA-1 · d-1; P < 0.001).

Conclusions

Enteroids recapitulate in vivo citrulline production and offer the opportunity to study the regulation of citrulline production in a highly manipulable system.

Selecting the Best: Evolutionary Engineering of Chemical Production in Microbes

Microbial cell factories have proven to be an economical means of production for many bulk, specialty, and fine chemical products. However, we still lack both a holistic understanding of organism physiology and the ability to predictively tune enzyme activities in vivo, thus slowing down rational engineering of industrially relevant strains. An alternative concept to rational engineering is to use evolution as the driving force to select for desired changes, an approach often described as evolutionary engineering. In evolutionary engineering, in vivo selections for a desired phenotype are combined with either generation of spontaneous mutations or some form of targeted or random mutagenesis. Evolutionary engineering has been used to successfully engineer easily selectable phenotypes, such as utilization of a suboptimal nutrient source or tolerance to inhibitory substrates or products. In this review, we focus primarily on a more challenging problem-the use of evolutionary engineering for improving the production of chemicals in microbes directly. We describe recent developments in evolutionary engineering strategies, in general, and discuss, in detail, case studies where production of a chemical has been successfully achieved through evolutionary engineering by coupling production to cellular growth.

Citrate chemistry and biology for biomaterials design

Leveraging the multifunctional nature of citrate in chemistry and inspired by its important role in biological tissues, a class of highly versatile and functional citrate-based materials (CBBs) has been developed via facile and cost-effective polycondensation. CBBs exhibiting tunable mechanical properties and degradation rates, together with excellent biocompatibility and processability, have been successfully applied in vitro and in vivo for applications ranging from soft to hard tissue regeneration, as well as for nanomedicine designs. We summarize in the review, chemistry considerations for CBBs design to tune polymer properties and to introduce functionality with a focus on the most recent advances, biological functions of citrate in native tissues with the new notion of degradation products as cell modulator highlighted, and the applications of CBBs in wound healing, nanomedicine, orthopedic, cardiovascular, nerve and bladder tissue engineering. Given the expansive evidence for citrate's potential in biology and biomaterial science outlined in this review, it is expected that citrate based materials will continue to play an important role in regenerative engineering.

Disease-related metabolites affect protein-nanoparticle interactions

Once in biological fluids, the surface of nanoparticles (NPs) is rapidly covered with a layer of biomolecules (i.e., the "protein corona") whose composition strongly determines their biological identity, regulates interactions with biological entities including cells and the immune system, and consequently directs the biological fate and pharmacokinetics of nanoparticles. We recently introduced the concept of a "personalized protein corona" which refers to the formation of different biological identities of the exact same type of NP after being exposed to extract plasmas from individuals who have various types of diseases. As different diseases have distinct metabolomic profiles and metabolites can interact with proteins, it is legitimate to hypothesize that metabolomic profiles in plasma may have the capacity to, at least partially, drive the formation of a personalized protein corona. To test this hypothesis, we employed a multi-scale approach composed of coarse-grained (CG) and all atom (AA) molecular dynamics (MD) simulations to probe the role of glucose and cholesterol (model metabolites in diabetes and hypercholesterolemia patients) in the interaction of fibrinogen protein and polystyrene NPs. Our results revealed that glucose and cholesterol had the capacity to induce substantial changes in the binding site of fibrinogen to the surface of NPs. More specifically, the simulation results demonstrated that increasing the metabolite amount could change the profiles of fibrinogen adsorption and replacement, what is known as the Vroman effect, on the NP surface. In addition, we also found out that metabolites can substantially determine the immune triggering potency of the fibrinogen-NP complex. Our proof-of-concept outcomes further emphasize the need for the development of patient-specific NPs in a disease type-specific manner for high yielding and safe clinical applications.

Deuterium- and Tritium-Labelled Compounds: Applications in the Life Sciences

Hydrogen isotopes are unique tools for identifying and understanding biological and chemical processes. Hydrogen isotope labelling allows for the traceless and direct incorporation of an additional mass or radioactive tag into an organic molecule with almost no changes in its chemical structure, physical properties, or biological activity. Using deuterium-labelled isotopologues to study the unique mass-spectrometric patterns generated from mixtures of biologically relevant molecules drastically simplifies analysis. Such methods are now providing unprecedented levels of insight in a wide and continuously growing range of applications in the life sciences and beyond. Tritium (³ H), in particular, has seen an increase in utilization, especially in pharmaceutical drug discovery. The efforts and costs associated with the synthesis of labelled compounds are more than compensated for by the enhanced molecular sensitivity during analysis and the high reliability of the data obtained. In this Review, advances in the application of hydrogen isotopes in the life sciences are described.

Experimental design and reporting standards for metabolomics studies of mammalian cell lines

Metabolomics is an analytical technique that investigates the small biochemical molecules present within a biological sample isolated from a plant, animal, or cultured cells. It can be an extremely powerful tool in elucidating the specific metabolic changes within a biological system in response to an environmental challenge such as disease, infection, drugs, or toxins. A historically difficult step in the metabolomics pipeline is in data interpretation to a meaningful biological context, for such high-variability biological samples and in untargeted metabolomics studies that are hypothesis-generating by design. One way to achieve stronger biological context of metabolomic data is via the use of cultured cell models, particularly for mammalian biological systems. The benefits of in vitro metabolomics include a much greater control of external variables and no ethical concerns. The current concerns are with inconsistencies in experimental procedures and level of reporting standards between different studies. This review discusses some of these discrepancies between recent studies, such as metabolite extraction and data normalisation. The aim of this review is to highlight the importance of a standardised experimental approach to any cultured cell metabolomics study and suggests an example procedure fully inclusive of information that should be disclosed in regard to the cell type/s used and their culture conditions. Metabolomics of cultured cells has the potential to uncover previously unknown information about cell biology, functions and response mechanisms, and so the accurate biological interpretation of the data produced and its ability to be compared to other studies should be considered vitally important.

Evolution of evolvability and phenotypic plasticity in virtual cells

BACKGROUND

Changing environmental conditions pose a challenge for the survival of species. To meet this challenge organisms adapt their phenotype by physiological regulation (phenotypic plasticity) or by evolving. Regulatory mechanisms that ensure a constant internal environment in the face of continuous external fluctuations (homeostasis) are ubiquitous and essential for survival. However, more drastic and enduring environmental change, often requires lineages to adapt by mutating. In vitro evolutionary experiments with microbes show that adaptive, large phenotypic changes occur remarkably quickly, requiring only a few mutations. It has been proposed that the high evolvability demonstrated by these microbes, is an evolved property. If both regulation (phenotypic plasticity) and evolvability can evolve as strategies to adapt to change, what are the conditions that favour the emergence of either of these strategy? Does evolution of one strategy hinder or facilitate evolution of the other strategy?

RESULTS

Here we investigate this with computational evolutionary modelling in populations of Virtual Cells. During a preparatory evolutionary phase, Virtual Cells evolved homeostasis regulation for internal metabolite concentrations in a fluctuating environment. The resulting wild-type Virtual Cell strains (WT-VCS) were then exposed to periodic, drastic environmental changes, while maintaining selection on homeostasis regulation. In different sets of simulations the nature and frequencies of environmental change were varied. Pre-evolved WT-VCS were highly evolvable, showing rapid evolutionary adaptation after novel environmental change. Moreover, continued low frequency changes resulted in evolutionary restructuring of the genome that enables even faster adaptation with very few mutations. In contrast, when change frequency is high, lineages evolve phenotypic plasticity that allows them to be fit in different environments without mutations. Yet, evolving phenotypic plasticity is a comparatively slow process. Under intermediate change frequencies, both strategies occur.

CONCLUSIONS

We conclude that evolving a homeostasis mechanisms predisposes lineage to be evolvable to novel environmental conditions. Moreover, after continued evolution, evolvability can be a viable alternative with comparable fitness to regulated phenotypic plasticity in all but the most rapidly changing environments.

Nucleoside Analogue Triphosphates Allosterically Regulate Human Ribonucleotide Reductase and Identify Chemical Determinants That Drive Substrate Specificity

Class I ribonucleotide reductase (RR) maintains balanced pools of deoxyribonucleotide substrates for DNA replication by converting ribonucleoside diphosphates (NDPs) to 2'-deoxyribonucleoside diphosphates (dNDPs). Binding of deoxynucleoside triphosphate (dNTP) effectors (ATP/dATP, dGTP, and dTTP) modulates the specificity of class I RR for CDP, UDP, ADP, and GDP substrates. Crystal structures of bacterial and eukaryotic RRs show that dNTP effectors and NDP substrates bind on either side of a flexible nine-amino acid loop (loop 2). Interactions with the effector nucleobase alter loop 2 geometry, resulting in changes in specificity among the four NDP substrates of RR. However, the functional groups proposed to drive specificity remain untested. Here, we use deoxynucleoside analogue triphosphates to determine the nucleobase functional groups that drive human RR (hRR) specificity. The results demonstrate that the 5-methyl, O4, and N3 groups of dTTP contribute to specificity for GDP. The O6 and protonated N1 of dGTP direct specificity for ADP. In contrast, the unprotonated N1 of adenosine is the primary determinant of ATP/dATP-directed specificity for CDP. Structural models from X-ray crystallography of eukaryotic RR suggest that the side chain of D287 in loop 2 is involved in binding of dGTP and dTTP, but not dATP/ATP. This feature is consistent with experimental results showing that a D287A mutant of hRR is deficient in allosteric regulation by dGTP and dTTP, but not ATP/dATP. Together, these data define the effector functional groups that are the drivers of human RR specificity and provide constraints for evaluating models of allosteric regulation.

Understanding Metabolic Regulation at a Systems Level: Metabolite Sensing, Mathematical Predictions, and Model Organisms

Metabolic networks are extensively regulated to facilitate tissue-specific metabolic programs and robustly maintain homeostasis in response to dietary changes. Homeostatic metabolic regulation is achieved through metabolite sensing coupled to feedback regulation of metabolic enzyme activity or expression. With a wealth of transcriptomic, proteomic, and metabolomic data available for different cell types across various conditions, we are challenged with understanding global metabolic network regulation and the resulting metabolic outputs. Stoichiometric metabolic network modeling integrated with "omics" data has addressed this challenge by generating nonintuitive, testable hypotheses about metabolic flux rewiring. Model organism studies have also yielded novel insight into metabolic networks. This review covers three topics: the feedback loops inherent in metabolic regulatory networks, metabolic network modeling, and interspecies studies utilizing Caenorhabditis elegans and various bacterial diets that have revealed novel metabolic paradigms.

Use of a Bacterial Luciferase Monitoring System To Estimate Real-Time Dynamics of Intracellular Metabolism in Escherichia coli

Regulation of central carbon metabolism has long been an important research subject in every organism. While the dynamics of metabolic flows during changes in available carbon sources have been estimated based on changes in metabolism-related gene expression, as well as on changes in the metabolome, the flux change itself has scarcely been measured because of technical difficulty, which has made conclusions elusive in many cases. Here, we used a monitoring system employing Vibrio fischeri luciferase to probe the intracellular metabolic condition in Escherichia coli Using a batch culture provided with a limited amount of glucose, we performed a time course analysis, where the predominant carbon source shifts from glucose to acetate, and identified a series of sequential peaks in the luciferase activity (peaks 1 to 4). Two major peaks, peaks 1 and 3, were considered to correspond to the glucose and acetate consuming phases, respectively, based on the glucose, acetate, and dissolved oxygen concentrations in the medium. The pattern of these peaks was changed by the addition of a different carbon source or by an increasing concentration of glucose, which was consistent with the present model. Genetically, mutations involved in glycolysis or the tricarboxylic acid (TCA) cycle/gluconeogenesis specifically affected peak 1 or peak 3, respectively, as expected from the corresponding metabolic phase. Intriguingly, mutants for the acetate excretion pathway showed a phenotype of extended peak 2 and delayed transition to the TCA cycle/gluconeogenesis phase, which suggests that peak 2 represents the metabolic transition phase. These results indicate that the bacterial luciferase monitoring system is useful to understand the real-time dynamics of metabolism in living bacterial cells.

IMPORTANCE

Intracellular metabolic flows dynamically change during shifts in available carbon sources. However, because of technical difficulty, the flux change has scarcely been measured in living cells. Here, we used a Vibrio fischeri luciferase monitoring system to probe the intracellular metabolic condition in Escherichia coli Using a limited amount of glucose batch culture, a series of sequential peaks (peaks 1 to 4) in the luciferase activity was observed. Changes in the pattern of these peaks by the addition of extra carbon sources and in mutant strains involved in glycolysis or the TCA cycle/gluconeogenesis gene assigned the metabolic phase corresponding to peak 1 as the glycolysis phase and peak 3 as the TCA cycle/gluconeogenesis phase. Intriguingly, the acetate excretion pathway engaged in peak 2 represents the metabolic transition phase. These results indicate that the bacterial luciferase monitoring system is useful to understand the real-time dynamics of metabolism in living bacterial cells.

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

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

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

BACKGROUND

Metabolism gained increasing interest for the understanding of diseases and to pinpoint therapeutic intervention points. However, classical metabolomics techniques only provide a very static view on metabolism. Metabolic flux analysis methods, on the other hand, are highly targeted and require detailed knowledge on metabolism beforehand.

RESULTS

We present a novel workflow to analyze non-targeted metabolome-wide stable isotope labeling data to detect metabolic flux changes in a non-targeted manner. Furthermore, we show how similarity-analysis of isotopic enrichment patterns can be used for pathway contextualization of unidentified compounds. We illustrate our approach with the analysis of changes in cellular metabolism of human adenocarcinoma cells in response to decreased oxygen availability. Starting without a priori knowledge, we detect metabolic flux changes, leading to an increased glutamine contribution to acetyl-CoA production, reveal biosynthesis of N-acetylaspartate by N-acetyltransferase 8-like (NAT8L) in lung cancer cells and show that NAT8L silencing inhibits proliferation of A549, JHH-4, PH5CH8, and BEAS-2B cells.

CONCLUSIONS

Differential stable isotope labeling analysis provides qualitative metabolic flux information in a non-targeted manner. Furthermore, similarity analysis of enrichment patterns provides information on metabolically closely related compounds. N-acetylaspartate and NAT8L are important players in cancer cell metabolism, a context in which they have not received much attention yet.

The role of HIF-1 in oncostatin M-dependent metabolic reprogramming of hepatic cells

BACKGROUND

Hypoxia and inflammation have been identified as hallmarks of cancer. A majority of hepatocellular carcinomas are preceded by hepatitis B- or C-related chronic infections suggesting that liver cancer development is promoted by an inflammatory microenvironment. The inflammatory cytokine oncostatin M (OSM) was shown to induce the expression of hypoxia-inducible factor-1 α (HIF-1 α) under normoxic conditions in hepatocytes and hepatoma cells. HIF-1 α is known to orchestrate the expression of numerous genes, many of which code for metabolic enzymes that play key roles in the adaptation of cellular metabolism to low oxygen tension.

RESULTS

Here, we show that OSM-induced upregulation of HIF-1 α reprograms cellular metabolism in three clones of the human hepatocyte cell line PH5CH (PH5CH1, PH5CH7, and PH5CH8) towards a hypoxia-like metabolic phenotype but has no significant effect on cellular metabolism of HepG2 and JHH-4 hepatoma cells. Although we observed only minor changes in glucose uptake and lactate secretion in PH5CH8 upon OSM treatment, we identified more pronounced changes in intracellular fluxes based on stable isotope labeling experiments. In particular, glucose oxidation in the tricarboxylic acid (TCA) cycle is reduced through pyruvate dehydrogenase kinase 1 (PDK1)-mediated inhibition of the pyruvate dehydrogenase complex, thereby reducing the oxidative TCA cycle flux. As a result of the impaired mitochondrial glucose and glutamine oxidation, the reductive isocitrate dehydrogenase flux was increased.

CONCLUSIONS

We provide evidence that connects the inflammatory mediator OSM to a hypoxia-like metabolic phenotype. In the human hepatocyte cell line PH5CH, OSM-mediated upregulation of HIF-1 α and PDK1 can induce hypoxia-like metabolic changes, although to a lesser extent than hypoxia itself. Since PDK1 is overexpressed in several cancers, it might provide a causal link between chronic inflammation and malignant cellular transformation.

Loss of DJ-1 impairs antioxidant response by altered glutamine and serine metabolism

The oncogene DJ-1 has been originally identified as a suppressor of PTEN. Further on, loss-of-function mutations have been described as a causative factor in Parkinson's disease (PD). DJ-1 has an important function in cellular antioxidant responses, but its role in central metabolism of neurons is still elusive. We applied stable isotope assisted metabolic profiling to investigate the effect of a functional loss of DJ-1 and show that DJ-1 deficient neuronal cells exhibit decreased glutamine influx and reduced serine biosynthesis. By providing precursors for GSH synthesis, these two metabolic pathways are important contributors to cellular antioxidant response. Down-regulation of these pathways, as a result of loss of DJ-1 leads to an impaired antioxidant response. Furthermore, DJ-1 deficient mouse microglia showed a weak but constitutive pro-inflammatory activation. The combined effects of altered central metabolism and constitutive activation of glia cells raise the susceptibility of dopaminergic neurons towards degeneration in patients harboring mutated DJ-1. Our work reveals metabolic alterations leading to increased cellular instability and identifies potential new intervention points that can further be studied in the light of novel translational medicine approaches.

Quantifying plant phenotypes with isotopic labeling & metabolic flux analysis

Analyses of metabolic flux using stable isotopes in plants have traditionally been restricted to tissues with presumed homogeneous cell populations and long metabolic steady states such as developing seeds, cell suspensions, or cultured roots and root tips. It is now possible to describe these and other metabolically more dynamic tissues such as leaves in greater detail using novel methods in mass spectrometry, isotope labeling strategies, and transient labeling-based flux analyses. Such studies are necessary for a systems level description of plant function that more closely represents biological reality, and provides insights into the genes that will need to be modified as natural resources become ever more limited and environments change.

Reconstruction and validation of a constraint-based metabolic network model for bone marrow-derived mesenchymal stem cells

OBJECTIVES

Over recent years, constraint-based modelling of metabolic networks has become increasingly popular; the models are suitable for system-level modelling of cell physiology. The goal of the present work was to reconstruct a constraint-based metabolic network model of bone marrow-derived mesenchymal stem cells (BMMSCs).

MATERIALS AND METHODS

To reconstruct a BMMSC-specific metabolic model, transcriptomic data of BMMSCs, and additionally, the human generic metabolic network model (Recon1) were used. Then, using the mCADRE algorithm, a draft metabolic network was reconstructed. Literature and proteomic data were subsequently used to refine and improve the draft. From this, iMSC1255 was derived to be the metabolic network model of BMMSCs.

RESULTS

iMSC1255 has 1255 genes, 1850 metabolites and 2288 reactions. After including additional constraints based on previously reported experimental results, our model successfully predicted BMMSC growth rate and metabolic phenotypes.

CONCLUSIONS

Here, iMSC1255 is introduced to be the metabolic network model of bone marrow-derived mesenchymal stem cells. Based on current knowledge, this is the first report on genome-scale reconstruction and validation of a stem cell metabolic network model.