The evolution of connectivity in metabolic networks

Processes in living cells are the result of interactions between biochemical compounds in highly complex biochemical networks. It is a major challenge in biology to understand causes and consequences of the specific design of these networks. A characteristic design feature of metabolic networks is the presence of hub metabolites such as ATP or NADH that are involved in a high number of reactions. To study the emergence of hub metabolites, we implemented computer simulations of a widely accepted scenario for the evolution of metabolic networks. Our simulations indicate that metabolic networks with a large number of highly specialized enzymes may evolve from a few multifunctional enzymes. During this process, enzymes duplicate and specialize, leading to a loss of biochemical reactions and intermediary metabolites. Complex features of metabolic networks such as the presence of hubs may result from selection of growth rate if essential biochemical mechanisms are considered. Specifically, our simulations indicate that group transfer reactions are essential for the emergence of hubs.     

Metabolic regulatory network alterations in response to acute cold stress and ginsenoside intervention

Acute stress may trigger systemic biochemical and physiological changes in living organisms, leading to a rapid loss of homeostasis, which can be gradually reinstated by self-regulatory mechanisms and/or drug intervention strategy. However, such a sophisticated metabolic regulatory process has so far been poorly understood, especially from a holistic view. Urinary metabolite profiling of Sprague-Dawley rats exposed to cold temperature (-10 degrees C) for 2 h using GC/MS in conjunction with modern multivariate statistical techniques revealed drastic biochemical changes as evidenced by fluctuations of urinary metabolites and demonstrated the protective effect of total ginsenosides (TGs) in ginseng extracts on stressed rats. The metabonomics approach enables us to visualize significant alterations in metabolite expression patterns as a result of stress-induced metabolic responses and post-stress compensation, and drug intervention. Several major metabolic pathways including catecholamines, glucocorticoids, the tricarboxylic acid (TCA) cycle, tryptophan (nicotinate), and gut microbiota metabolites were identified to be involved in metabolic regulation and compensation required to restore homeostasis.     

Constructing de novo biosynthetic pathways for chemical synthesis inside living cells

Living organisms have evolved a vast array of catalytic functions that make them ideally suited for the production of medicinally and industrially relevant small-molecule targets. Indeed, native metabolic pathways in microbial hosts have long been exploited and optimized for the scalable production of both fine and commodity chemicals. Our increasing capacity for DNA sequencing and synthesis has revealed the molecular basis for the biosynthesis of a variety of complex and useful metabolites and allows the de novo construction of novel metabolic pathways for the production of new and exotic molecular targets in genetically tractable microbes. However, the development of commercially viable processes for these engineered pathways is currently limited by our ability to quickly identify or engineer enzymes with the correct reaction and substrate selectivity as well as the speed by which metabolic bottlenecks can be determined and corrected. Efforts to understand the relationship among sequence, structure, and function in the basic biochemical sciences can advance these goals for synthetic biology applications while also serving as an experimental platform for elucidating the in vivo specificity and function of enzymes and reconstituting complex biochemical traits for study in a living model organism. Furthermore, the continuing discovery of natural mechanisms for the regulation of metabolic pathways has revealed new principles for the design of high-flux pathways with minimized metabolic burden and has inspired the development of new tools and approaches to engineering synthetic pathways in microbial hosts for chemical production.     

A network-based method for target selection in metabolic networks

MOTIVATION: The lack of new antimicrobials, combined with increasing microbial resistance to old ones, poses a serious threat to public health. With hundreds of genomes sequenced, systems biology promises to help in solving this problem by uncovering new drug targets. RESULTS: Here, we propose an approach that is based on the mapping of the interactions between biochemical agents, such as proteins and metabolites, onto complex networks. We report that nodes and links in complex biochemical networks can be grouped into a small number of classes, based on their role in connecting different functional modules. Specifically, for metabolic networks, in which nodes represent metabolites and links represent enzymes, we demonstrate that some enzyme classes are more likely to be essential, some are more likely to be species-specific and some are likely to be both essential and specific. Our network-based enzyme classification scheme is thus a promising tool for the identification of drug targets. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

A global reorganization of the metabolome in Arabidopsis during cold acclimation is revealed by metabolic fingerprinting

Many plants, including Arabidopsis , increase their freezing tolerance in response to low, non-freezing temperatures. This process is known as cold acclimation and involves many complex biochemical changes at the level of the metabolome. Our goal was to examine the effects of cold acclimation on the metabolome using a non-targeted metabolic fingerprinting approach. Multivariate data analyses indicate that, in Arabidopsis, a global reprogramming of metabolism occurs as a result of cold acclimation. By measuring an entire spectrum of putative metabolites based on mass-to-charge ( m / z ) ratios, vs. an individual or group of metabolite(s), a comprehensive, unbiased assessment of metabolic processes relative to cold acclimation was determined. Whereas leaves shifted to low temperature present metabolic profiles that are constantly changing, leaves developed at low temperature demonstrate a stable complement of components. Although it appears that some metabolic networks are modulated by the environment, others require development under low-temperature conditions for adjustment. Understanding how metabolism as a whole is regulated allows the integration of cellular, physiological and ecological attributes in a biological system, a necessity if complex traits, such as freezing tolerance, are to be modified by breeding or genetic manipulation.     

Genetic engineering of polyamine and carbohydrate metabolism for osmotic stress tolerance in higher plants

Plant growth and productivity are greatly affected by various stress factors. The molecular mechanisms of stress tolerance in plant species have been well established. Metabolic pathways involving the synthesis of metabolites such as polyamines, carbohydrates, proline and glycine betaine have been shown to be associated with stress tolerance. Introduction of the stress-induced genes involved in these pathways from tolerant species to sensitive plants seems to be a promising approach to confer stress tolerance in plants. In cases where single gene is not enough to confer tolerance, metabolic engineering necessitates the introduction of multiple transgenes in plants.     

Metabolic engineering: techniques for analysis of targets for genetic manipulations

Metabolic engineering has been defined as the purposeful modification of intermediary metabolism using recombinant DNA techniques. With this definition metabolic engineering includes: (1) inserting new pathways in microorganisms with the aim of producing novel metabolites, e.g., production of polyketides by Streptomyces; (2) production of heterologous peptides, e.g., production of human insulin, erythropoitin, and tPA; and (3) improvement of both new and existing processes, e.g., production of antibiotics and industrial enzymes. Metabolic engineering is a multidisciplinary approach, which involves input from chemical engineers, molecular biologists, biochemists, physiologists, and analytical chemists. Obviously, molecular biology is central in the production of novel products, as well as in the improvement of existing processes. However, in the latter case, input from other disciplines is pivotal in order to target the genetic modifications; with the rapid developments in molecular biology, progress in the field is likely to be limited by procedures to identify the optimal genetic changes. Identification of the optimal genetic changes often requires a meticulous mapping of the cellular metabolism at different operating conditions, and the application of metabolic engineering to process optimization is, therefore, expected mainly to have an impact on the improvement of processes where yield, productivity, and titer are important design factors, i.e., in the production of metabolites and industrial enzymes. Despite the prospect of obtaining major improvement through metabolic engineering, this approach is, however, not expected to completely replace the classical approach to strain improvement-random mutagenesis followed by screening. Identification of the optimal genetic changes for improvement of a given process requires analysis of the underlying mechanisms, at best, at the molecular level. To reveal these mechanisms a number of different techniques may be applied: (1) detailed physiological studies, (2) metabolic flux analysis (MFA), (3) metabolic control analysis (MCA), (4) thermodynamic analysis of pathways, and (5) kinetic modeling. In this article, these different techniques are discussed and their applications to the analysis of different processes are illustrated.     

Metabolic networks: enzyme function and metabolite structure

Metabolism is one of the most complex cellular processes. Connections between biochemical reactions via substrate and product metabolites create complex metabolic networks that may be analyzed using network theory, stoichiometric analysis, and information on protein structure/function and metabolite properties. These frameworks take into consideration different aspects of enzyme chemistry, enzyme structure and metabolite structure, and demonstrate the impact of metabolic biochemistry on the systemic properties of metabolism. The integration of these approaches and the systematic classification of enzyme function and the chemical structure of metabolites will enhance our understanding of metabolism, and could improve our ability to predict enzyme function and novel metabolic pathways.     

A network perspective on metabolism and aging

Aging affects a myriad of genetic, biochemical, and metabolic processes, and efforts to understand the underlying molecular basis of aging are often thwarted by the complexity of the aging process. By taking a systems biology approach, network analysis is well-suited to study the decline in function with age. Network analysis has already been utilized in describing other complex processes such as development, evolution, and robustness. Networks of gene expression and protein-protein interaction have provided valuable insight into the loss of connectivity and network structure throughout lifespan. Here, we advocate the use of metabolic networks to expand the work from genomics and proteomics. As metabolism is the final fingerprint of functionality and has been implicated in multiple theories of aging, metabolomic methods combined with metabolite network analyses should pave the way to investigate how relationships of metabolites change with age and how these interactions affect phenotype and function of the aging individual. The metabolomic network approaches highlighted in this review are fundamental for an understanding of systematic declines and of failure to function with age.     

Signatures of Arithmetic Simplicity in Metabolic Network Architecture

Metabolic networks perform some of the most fundamental functions in living cells, including energy transduction and building block biosynthesis. While these are the best characterized networks in living systems, understanding their evolutionary history and complex wiring constitutes one of the most fascinating open questions in biology, intimately related to the enigma of life''s origin itself. Is the evolution of metabolism subject to general principles, beyond the unpredictable accumulation of multiple historical accidents? Here we search for such principles by applying to an artificial chemical universe some of the methodologies developed for the study of genome scale models of cellular metabolism. In particular, we use metabolic flux constraint-based models to exhaustively search for artificial chemistry pathways that can optimally perform an array of elementary metabolic functions. Despite the simplicity of the model employed, we find that the ensuing pathways display a surprisingly rich set of properties, including the existence of autocatalytic cycles and hierarchical modules, the appearance of universally preferable metabolites and reactions, and a logarithmic trend of pathway length as a function of input/output molecule size. Some of these properties can be derived analytically, borrowing methods previously used in cryptography. In addition, by mapping biochemical networks onto a simplified carbon atom reaction backbone, we find that properties similar to those predicted for the artificial chemistry hold also for real metabolic networks. These findings suggest that optimality principles and arithmetic simplicity might lie beneath some aspects of biochemical complexity.     

Hairy Roots, their Multiple Applications and Recent Patents

In the last years, hairy root (HR) cultures are gaining attention in the biotechnology industry. This particular plant cell culture derives from explants infected with Agrobacterium rhizogenes. They constitute a relatively new approach to in vitro plant biotechnology and modern HR cultures are far away from the valuables findings performed by Philip R. White in the 1930?s, who obtained indefinite growth of excised root tips. HR cultures are characterized by genetic and biochemical stability and high growth rate without expensive exogenous hormones source. HR cultures have allowed a deep study of plant metabolic pathways and the production of valuable secondary metabolites and enzymes, with therapeutic or industrial application. Furthermore, the potential of HR cultures is increasing continuously since different biotechnological strategies such as genetic engineering, elicitation and metabolic traps are currently being explored for discovery of new metabolites and pathways, as well as for increasing metabolites biosynthesis and/or secretion. Advances in design of proper bioreactors for HR growth are being of great interest, since scale up of metabolite production will allow the integration of this technology to industrial processes. Another application of HR cultures is related to their capabilities to biotransform and to degrade different xenobiotics. In this context, removal assays using this plant model system are useful tools for phytoremediation assays, previous to the application in the field. This review highlights the more recent application of HRs and those new patents which show their multiple utilities.     

Selfish cellular networks and the evolution of complex organisms

Human gametogenesis takes years and involves many cellular divisions, particularly in males. Consequently, gametogenesis provides the opportunity to acquire multiple de novo mutations. A significant portion of these is likely to impact the cellular networks linking genes, proteins, RNA and metabolites, which constitute the functional units of cells. A wealth of literature shows that these individual cellular networks are complex, robust and evolvable. To some extent, they are able to monitor their own performance, and display sufficient autonomy to be termed "selfish". Their robustness is linked to quality control mechanisms which are embedded in and act upon the individual networks, thereby providing a basis for selection during gametogenesis. These selective processes are equally likely to affect cellular functions that are not gamete-specific, and the evolution of the most complex organisms, including man, is therefore likely to occur via two pathways: essential housekeeping functions would be regulated and evolve during gametogenesis within the parents before being transmitted to their progeny, while classical selection would operate on other traits of the organisms that shape their fitness with respect to the environment.     

Rethinking glycolysis: on the biochemical logic of metabolic pathways

Metabolic pathways may seem arbitrary and unnecessarily complex. In many cases, a chemist might devise a simpler route for the biochemical transformation, so why has nature chosen such complex solutions? In this review, we distill lessons from a century of metabolic research and introduce new observations suggesting that the intricate structure of metabolic pathways can be explained by a small set of biochemical principles. Using glycolysis as an example, we demonstrate how three key biochemical constraints--thermodynamic favorability, availability of enzymatic mechanisms and the physicochemical properties of pathway intermediates--eliminate otherwise plausible metabolic strategies. Considering these constraints, glycolysis contains no unnecessary steps and represents one of the very few pathway structures that meet cellular demands. The analysis presented here can be applied to metabolic engineering efforts for the rational design of pathways that produce a desired product while satisfying biochemical constraints.     

Metabolite profiling of 5′-AMP induced hypometabolism

We have previously demonstrated that 5′-adenosine monophosphate (5′-AMP) can be used to induce deep hypometabolism in mice and other non-hibernating mammals. This reversible 5′-AMP induced hypometabolism (AIHM) allows mice to maintain a body temperature about 1 °C above the ambient temperature for several hours before spontaneous reversal to euthermia. Our biochemical and gene expression studies suggested that the molecular processes involved in AIHM behavior most likely occur at the metabolic interconversion level, rather than the gene or protein expression level. To understand the metabolic processes involved in AIHM behavior, we conducted a non-targeted comparative metabolomics investigation at multiple stages of AIHM in the plasma, liver and brain of animals that underwent AIHM. Dozens of metabolites representing many important metabolic pathways were detected and measured using a metabolite profiling platform combining both liquid-chromatography–mass spectrometry and gas-chromatography–mass spectrometry. Our findings indicate that there is a widespread suppression of energy generating metabolic pathways but lipid metabolism appears to be minimally altered. Regulation of carbohydrate metabolites appears to be the major way the animal utilizes energy in AIHM and during the following recovery process. The 5′-AMP administered has largely been catabolized by the time the animals have entered AIHM. During AIHM, the urea cycle appears to be functional, helping to avoid ammonia toxicity. Of all tissues studied, brain’s metabolite flux is the least affected by AIHM.