Metabolic networks are NP-hard to reconstruct

High-throughput data from various omics and sequencing techniques have rendered the automated metabolic network reconstruction a highly relevant problem. Our approach reflects the inherent probabilistic nature of the steps involved in metabolic network reconstruction. Here, the goal is to arrive at networks which combine probabilistic information with the possibility to obtain a small number of disconnected network constituents by reduction of a given preliminary probabilistic metabolic network. We define automated metabolic network reconstruction as an optimization problem on four-partite graph (nodes representing genes, enzymes, reactions, and metabolites) which integrates: (1) probabilistic information obtained from the existing process for metabolic reconstruction from a given genome, (2) connectedness of the raw metabolic network, and (3) clustering of components in the reconstructed metabolic network. The practical implications of our theoretical analysis refer to the quality of reconstructed metabolic networks and shed light on the problem of finding more efficient and effective methods for automated reconstruction. Our main contributions include: a completeness result for the defined problem, polynomial-time approximation algorithm, and an optimal polynomial-time algorithm for trees. Moreover, we exemplify our approach by the reconstruction of the sucrose biosynthesis pathway in Chlamydomonas reinhardtii.     

Metabolic engineering of Bacillus subtilis fueled by systems biology: Recent advances and future directions

By combining advanced omics technology and computational modeling, systems biologists have identified and inferred thousands of regulatory events and system-wide interactions of the bacterium Bacillus subtilis, which is commonly used both in the laboratory and in industry. This dissection of the multiple layers of regulatory networks and their interactions has provided invaluable information for unraveling regulatory mechanisms and guiding metabolic engineering. In this review, we discuss recent advances in the systems biology and metabolic engineering of B. subtilis and highlight current gaps in our understanding of global metabolism and global pathway engineering in this organism. We also propose future perspectives in the systems biology of B. subtilis and suggest ways that this approach can be used to guide metabolic engineering. Specifically, although hundreds of regulatory events have been identified or inferred via systems biology approaches, systematic investigation of the functionality of these events in vivo has lagged, thereby preventing the elucidation of regulatory mechanisms and further rational pathway engineering. In metabolic engineering, ignoring the engineering of multilayer regulation hinders metabolic flux redistribution. Post-translational engineering, allosteric engineering, and dynamic pathway analyses and control will also contribute to the modulation and control of the metabolism of engineered B. subtilis, ultimately producing the desired cellular traits. We hope this review will aid metabolic engineers in making full use of available systems biology datasets and approaches for the design and perfection of microbial cell factories through global metabolism optimization.     

Effects of harvest dates on microbial communities of ice grape skins from Xinjiang of China

Ice wine is a sweet dessert wine made from pressing grapes naturally frozen on the vines. The structure and metabolic characteristics of native microbial community dominated by organics and nutrients transformation in fermenting process of ice wine on the grape skin are likely to change due to climate events. Our objective was to evaluate the influence of harvest time on structure and metabolic characteristics of bacterial and fungal communities on Vidal ice grape surface. Vidal grape samples were picked between October and December in 2018; Harvest 1 (VG1): 14 October; Harvest 2 (VG2): 16 November; Harvest 3 (VG3): 18 December. Vishniacozyma, Alternaria, Cladosporium, Stenotrophomonas, unidentified_Cyanobacteria and Sphingomonas existed in all harvest dates and were the main genera widespread in most grape samples from the three harvest periods. Saprotrophic fungi and bacteria involved in metabolism were also dominant. For fungi, wood saprotrophs and unidentified saprotrophs were detected comprising Phoma, Didymella, Filobasidium and Clavaria. Delayed harvest of ice grapes has a distinct advantage for pathogen reduction compared with that of normally harvested grapes. Among bacteria, the most frequently occurring types in the metabolism category were energy metabolism, carbohydrate metabolism and lipid metabolism. In short, the harvest period can positively regulate the function of Vidal ice grape epidermal microorganisms.     

In Silico Models for Dynamic Connected Cell Cultures Mimicking Hepatocyte-Endothelial Cell-Adipocyte Interaction Circle

The biochemistry of a system made up of three kinds of cell is virtually impossible to work out without the use of in silico models. Here, we deal with homeostatic balance phenomena from a metabolic point of view and we present a new computational model merging three single-cell models, already available from our research group: the first model reproduced the metabolic behaviour of a hepatocyte, the second one represented an endothelial cell, and the third one described an adipocyte. Multiple interconnections were created among these three models in order to mimic the main physiological interactions that are known for the examined cell phenotypes. The ultimate aim was to recreate the accomplishment of the homeostatic balance as it was observed for an in vitro connected three-culture system concerning glucose and lipid metabolism in the presence of the medium flow. The whole model was based on a modular approach and on a set of nonlinear differential equations implemented in Simulink, applying Michaelis-Menten kinetic laws and some energy balance considerations to the studied metabolic pathways. Our in silico model was then validated against experimental datasets coming from literature about the cited in vitro model. The agreement between simulated and experimental results was good and the behaviour of the connected culture system was reproduced through an adequate parameter evaluation. The developed model may help other researchers to investigate further about integrated metabolism and the regulation mechanisms underlying the physiological homeostasis.     

Glycogen and Glucose Metabolism Are Essential for Early Embryonic Development of the Red Flour Beetle Tribolium castaneum

Control of energy metabolism is an essential process for life. In insects, egg formation (oogenesis) and embryogenesis is dependent on stored molecules deposited by the mother or transcribed later by the zygote. In oviparous insects the egg becomes an isolated system after egg laying with all energy conversion taking place during embryogenesis. Previous studies in a few vector species showed a strong correlation of key morphogenetic events and changes in glucose metabolism. Here, we investigate glycogen and glucose metabolism in the red flour beetle Tribolium castaneum, an insect amenable to functional genomic studies. To examine the role of the key enzymes on glycogen and glucose regulation we cloned and analyzed the function of glycogen synthase kinase 3 (GSK-3) and hexokinase (HexA) genes during T. castaneum embryogenesis. Expression analysis via in situ hybridization shows that both genes are expressed only in the embryonic tissue, suggesting that embryonic and extra-embryonic cells display different metabolic activities. dsRNA adult female injection (parental RNAi) of both genes lead a reduction in egg laying and to embryonic lethality. Morphological analysis via DAPI stainings indicates that early development is impaired in Tc-GSK-3 and Tc-HexA1 RNAi embryos. Importantly, glycogen levels are upregulated after Tc-GSK-3 RNAi and glucose levels are upregulated after Tc-HexA1 RNAi, indicating that both genes control metabolism during embryogenesis and oogenesis, respectively. Altogether our results show that T. castaneum embryogenesis depends on the proper control of glucose and glycogen.     

Metabonomic studies on potential plasma biomarkers in rats exposed to ionizing radiation and the protective effects of Hong Shan Capsule

An ultra performance liquid chromatography coupled to mass spectrometry-based metabonomic approach, combined with pattern recognition methods including PCA, PLS-DA, RF and heatmap, has been developed to characterize the global serum metabolic profile associated with ionizing radiation (IR). As the VIP-value threshold cutoff of the metabolites was set to 2, metabolites above this threshold were filtered out as potential target biomarkers. Nineteen distinct potential biomarkers in rat plasma were identified. To further elucidate the pathophysiology of IR, related metabolic pathways have been studied. It was found that IR was closely related to disturbed fatty acid metabolism, taurine and hypotaurine metabolism, sphingolipid metabolism, purine metabolism, pyrimidine metabolism, phospholipid catabolism, tryptophan metabolism, phenylalanine metabolism, and bile acid metabolism. With the presented metabonomic method, we systematically analyzed the protective effects of Traditional Chinese Medicine Hong Shan Capsule (HSC). The results demonstrated that HSC administration could provide satisfactory effects on IR through partially regulating the perturbed metabolic pathways.     

Construction and Analysis of the Model of Energy Metabolism in E. coli

Genome-scale models of metabolism have only been analyzed with the constraint-based modelling philosophy and there have been several genome-scale gene-protein-reaction models. But research on the modelling for energy metabolism of organisms just began in recent years and research on metabolic weighted complex network are rare in literature. We have made three research based on the complete model of E. coli’s energy metabolism. We first constructed a metabolic weighted network using the rates of free energy consumption within metabolic reactions as the weights. We then analyzed some structural characters of the metabolic weighted network that we constructed. We found that the distribution of the weight values was uneven, that most of the weight values were zero while reactions with abstract large weight values were rare and that the relationship between w (weight values) and v (flux values) was not of linear correlation. At last, we have done some research on the equilibrium of free energy for the energy metabolism system of E. coli. We found that (free energy rate input from the environment) can meet the demand of (free energy rate dissipated by chemical process) and that chemical process plays a great role in the dissipation of free energy in cells. By these research and to a certain extend, we can understand more about the energy metabolism of E. coli.     

Diffusional constraints on energy metabolism in skeletal muscle

Aerobic metabolic flux depends on the diffusion of high-energy phosphate molecules (e.g., ATP and phosphocreatine) from the mitochondria to cellular ATPases, as well as the diffusion of other molecules (e.g., ADP, Pi) back to the mitochondria. Here, we develop an approach for evaluating the influence of intracellular metabolite diffusion on skeletal muscle aerobic metabolism through the application of the effectiveness factor (η). This parameter provides an intuitive and informative means of quantifying the extent to which diffusion limits metabolic flux. We start with the classical approach assuming an infinite supply of substrate at the fiber boundary, and we expand this model to ultimately include nonlinear boundary and homogeneous reactions. Comparison of the model with experimental data from a wide range of skeletal muscle types reveals that most muscle fibers are not substantially limited by diffusion (η close to unity), but many are on the brink of rather substantial diffusion limitation. This implies that intracellular metabolite diffusion does not dramatically limit aerobic metabolic flux in most fibers, but it likely plays a role in limiting the evolution of muscle fiber design and function.     

Yeast “Make-Accumulate-Consume” Life Strategy Evolved as a Multi-Step Process That Predates the Whole Genome Duplication

When fruits ripen, microbial communities start a fierce competition for the freely available fruit sugars. Three yeast lineages, including baker’s yeast Saccharomyces cerevisiae, have independently developed the metabolic activity to convert simple sugars into ethanol even under fully aerobic conditions. This fermentation capacity, named Crabtree effect, reduces the cell-biomass production but provides in nature a tool to out-compete other microorganisms. Here, we analyzed over forty Saccharomycetaceae yeasts, covering over 200 million years of the evolutionary history, for their carbon metabolism. The experiments were done under strictly controlled and uniform conditions, which has not been done before. We show that the origin of Crabtree effect in Saccharomycetaceae predates the whole genome duplication and became a settled metabolic trait after the split of the S. cerevisiae and Kluyveromyces lineages, and coincided with the origin of modern fruit bearing plants. Our results suggest that ethanol fermentation evolved progressively, involving several successive molecular events that have gradually remodeled the yeast carbon metabolism. While some of the final evolutionary events, like gene duplications of glucose transporters and glycolytic enzymes, have been deduced, the earliest molecular events initiating Crabtree effect are still to be determined.     

Rewiring yeast metabolism to synthesize products beyond ethanol

Saccharomyces cerevisiae, Baker's yeast, is the industrial workhorse for producing ethanol and the subject of substantial metabolic engineering research in both industry and academia. S. cerevisiae has been used to demonstrate production of a wide range of chemical products from glucose. However, in many cases, the demonstrations report titers and yields that fall below thresholds for industrial feasibility. Ethanol synthesis is a central part of S. cerevisiae metabolism, and redirecting flux to other products remains a barrier to industrialize strains for producing other molecules. Removing ethanol producing pathways leads to poor fitness, such as impaired growth on glucose. Here, we review metabolic engineering efforts aimed at restoring growth in non-ethanol producing strains with emphasis on relieving glucose repression associated with the Crabtree effect and rewiring metabolism to provide access to critical cellular building blocks. Substantial progress has been made in the past decade, but many opportunities for improvement remain.     

Quantitative lipidomics reveals age-dependent perturbations of whole-body lipid metabolism in ACBP deficient mice

The acyl-CoA binding protein (ACBP) plays a key role in chaperoning long-chain acyl-CoAs into lipid metabolic processes and acts as an important regulatory hub in mammalian physiology. This is highlighted by the recent finding that mice devoid of ACBP suffer from a compromised epidermal barrier and delayed weaning, the physiological process where newborns transit from a fat-based milk diet to a carbohydrate-rich diet. To gain insights into how ACBP impinges on weaning and the concomitant remodeling of whole-body lipid metabolism we performed a comparative lipidomics analysis charting the absolute abundance of 613 lipid molecules in liver, muscle and plasma from weaning and adult Acbp knockout and wild type mice. Our results reveal that ACBP deficiency affects primarily lipid metabolism of liver and plasma during weaning. Specifically, we show that ACBP deficient mice have elevated levels of hepatic cholesteryl esters, and that lipids featuring an 18:1 fatty acid moiety are increased in Acbp depleted mice across all tissues investigated. Our results also show that the perturbation of systemic lipid metabolism in Acbp knockout mice is transient and becomes normalized and similar to that of wild type as mice grow older. These findings demonstrate that ACBP serves crucial functions in maintaining lipid metabolic homeostasis in mice during weaning.     

The Evolution of Fungal Metabolic Pathways

Fungi contain a remarkable range of metabolic pathways, sometimes encoded by gene clusters, enabling them to digest most organic matter and synthesize an array of potent small molecules. Although metabolism is fundamental to the fungal lifestyle, we still know little about how major evolutionary processes, such as gene duplication (GD) and horizontal gene transfer (HGT), have interacted with clustered and non-clustered fungal metabolic pathways to give rise to this metabolic versatility. We examined the synteny and evolutionary history of 247,202 fungal genes encoding enzymes that catalyze 875 distinct metabolic reactions from 130 pathways in 208 diverse genomes. We found that gene clustering varied greatly with respect to metabolic category and lineage; for example, clustered genes in Saccharomycotina yeasts were overrepresented in nucleotide metabolism, whereas clustered genes in Pezizomycotina were more common in lipid and amino acid metabolism. The effects of both GD and HGT were more pronounced in clustered genes than in their non-clustered counterparts and were differentially distributed across fungal lineages; specifically, GD, which was an order of magnitude more abundant than HGT, was most frequently observed in Agaricomycetes, whereas HGT was much more prevalent in Pezizomycotina. The effect of HGT in some Pezizomycotina was particularly strong; for example, we identified 111 HGT events associated with the 15 Aspergillus genomes, which sharply contrasts with the 60 HGT events detected for the 48 genomes from the entire Saccharomycotina subphylum. Finally, the impact of GD within a metabolic category was typically consistent across all fungal lineages, whereas the impact of HGT was variable. These results indicate that GD is the dominant process underlying fungal metabolic diversity, whereas HGT is episodic and acts in a category- or lineage-specific manner. Both processes have a greater impact on clustered genes, suggesting that metabolic gene clusters represent hotspots for the generation of fungal metabolic diversity.     

pH-induced gene regulation of solvent production by Clostridium acetobutylicum in continuous culture: Parameter estimation and sporulation modelling

The acetone–butanol (AB) fermentation process in the anaerobic endospore-forming Gram-positive bacterium Clostridium acetobutylicum is useful as a producer of biofuels, particularly butanol. Recent work has concentrated on trying to improve the efficiency of the fermentation method, either through changes in the environmental conditions or by modifying the genome to selectively favour the production of one particular solvent over others. Fermentation of glucose by C. acetobutylicum occurs in two stages: initially the acids acetate and butyrate are produced and excreted and then, as the external pH falls, acetate and butyrate are ingested and further metabolised into the solvents acetone, butanol and ethanol. In order to optimise butanol production, it is important to understand how pH affects the enzyme-controlled reactions in the metabolism process. We adapt an ordinary differential equation model of the metabolic network with regulation at the genetic level for the required enzymes; parametrising the model using experimental data generated from continuous culture, we improve on previous point predictions (S. Haus, S. Jabbari, T. Millat, H. Janssen, R.-J. Fisher, H. Bahl, J. R. King, O. Wolkenhauer, A systems biology approach to investigate the effect of pH-induced gene regulation on solvent production by Clostridium acetobutylicum in continuous culture, BMC Systems Biology 5 (2011)) [1] both by using a different optimisation approach and by computing confidence intervals and correlation coefficients. We find in particular that the parameters are ill-determined from the data and that two separate clusters of parameters appear correlated, reflecting the importance of two metabolic intermediates. We extend the model further to include another aspect of the clostridial survival mechanism, sporulation, and by computation of the Akaike Information Criterion values find that the there is some evidence for the presence of sporulation during the shift.     

Global Metabolomic Profiling of Mice Brains following Experimental Infection with the Cyst-Forming Toxoplasma gondii

The interplay between the Apicomplexan parasite Toxoplasma gondii and its host has been largely studied. However, molecular changes at the metabolic level in the host central nervous system and pathogenesis-associated metabolites during brain infection are largely unexplored. We used a global metabolomics strategy to identify differentially regulated metabolites and affected metabolic pathways in BALB/c mice during infection with T. gondii Pru strain at 7, 14 and 21 days post-infection (DPI). The non-targeted Liquid Chromatography-Mass Spectrometry (LC-MS) metabolomics analysis detected approximately 2,755 retention time-exact mass pairs, of which more than 60 had significantly differential profiles at different stages of infection. These include amino acids, organic acids, carbohydrates, fatty acids, and vitamins. The biological significance of these metabolites is discussed. Principal Component Analysis and Orthogonal Partial Least Square-Discriminant Analysis showed the metabolites’ profile to change over time with the most significant changes occurring at 14 DPI. Correlated metabolic pathway imbalances were observed in carbohydrate metabolism, lipid metabolism, energetic metabolism and fatty acid oxidation. Eight metabolites correlated with the physical recovery from infection-caused illness were identified. These findings indicate that global metabolomics adopted in this study is a sensitive approach for detecting metabolic alterations in T. gondii-infected mice and generated a comparative metabolic profile of brain tissue distinguishing infected from non-infected host.     

Exploring the relationship between bacterial genera and lipid metabolism in bovine rumen

The rumen is characterised by a complex microbial ecosystem, which is particularly active in lipid metabolism. Several studies demonstrated a role of diet and breed on bacterial community profile, with the effect on metabolic pathways. Despite the knowledge achieved on metabolism and the bacterial profile, little is known about the relationship between individual bacteria and metabolic pathways. Therefore, a multivariate approach was used to search for possible relationships between bacteria and products of several pathways. The correlation between rumen bacterial community composition and rumen lipid metabolism was assessed in 40 beef steers (20 Maremmana and 20 Aubrac) reared with the same system and fed the same diet. A canonical discriminant analysis combined with a canonical correlation analysis (CCA) was performed to explore this correlation. The variables showing a Pearson correlation higher than 0.6 as absolute value and significant were retained for CCA considering the relationship of bacterial composition with several metabolic pathways. The results indicated that some bacterial genera could have significant impacts on the presence of several fatty acids. However, the relationship between genera and fatty acid changes according to the breed, demonstrating that the metabolic pathways change according to the host genetic background, related to breed evolution, although there is also an intra-breed genetic background which should not be ignored. In Maremmana, Succiniclasticum and Rikenellaceae_RC9_gut_group showed a high positive correlation with dimethylacetals (DMAs) DMA_C13:0, DMA_C14:0, DMA_C14:0iso, DMA_C15:0, DMA_C15:0iso, and DMA_C18:0. Prevotellaceae_UCG-003 correlates with C18:3c9c12c15 and C18:1t11, while Fibrobacter and Succiniclasticum correlate with C18:2c9t11 and Lachnospiraceae_NK3A20_group correlates with C18:1c12. Prevotellaceae_UCG-003, Ruminococcaceae_UCG-010, and Oribacterium showed a positive correlation with C13:0iso, and C17:0. Conversely, in Aubrac, Treponema_2 and Rikenellaceae_RC9_gut_group correlated with DMA_C14:0iso, DMA_C16:0iso, DMA_C17:0iso, while Ruminococcaceae_UCG-010, Christensenellaceae_R-7_group and Ruminococcaceae_NK4A214_group correlated with DMA_C18:1t11, DMA_C14:0, DMA_C18:1c12. Acetitomaculum correlated with C18:2c9c12, C18:1c12, C18:1c13, C18:1t12 and Lachnospiraceae_NK3A20_group with C18:1t6-8 and C18:1t9. Saccharofermentas, Ruminococcaceae_UCG-010 and Rikenellaceae_RC9_gut_group correlated with C18:2c9t11 while, Prevotellaceae_UCG-001 and Ruminococcus_1 correlated with C14:0iso, C15:0, C15:0iso, C17:0. Saccharofermentans, Rikenellaceae_RC9_gut_group, Ruminococcaceae_NK4A214_group, and Ruminococcaceae_UCG-010 correlated with C13:1c12 and C16:0iso. These results lead to hypothesise a possible association between several metabolic pathways and one or a few bacterial genera. If these associations are confirmed by further investigations that verify the causality of a bacterial genus with a particular metabolic process, it will be possible to deepen the knowledge on the activity of the rumen population in lipid metabolism. This approach appears to be a promising tool for uncovering the correlation between bacterial genera and products of rumen lipid metabolism.