Increasing the flux in metabolic pathways: A metabolic control analysis perspective

Current perspective in research and industrial applications of microbial cellulases

The natural interactions between various bacteria, fungi, and other cellulolytic microorganisms destroy lignocellulosic polymers. The efficacy of this process is determined by the combined action of three main enzymes: endoglucanases, exo-glucanases, and β-glucosidase. The enzyme attacks the polymeric structure's β-1,4-linkages during the cellulose breakdown reaction. This mechanism is crucial for the environment as it recycles cellulose in the biosphere. However, there are problems with enzymatic cellulose breakdown, including complex cellulase structure, insufficient degradation efficacy, high production costs, and post-translational alterations, many of which are closely related to certain unidentified cellulase properties. These issues impede the practical use of cellulases. A developing area of research is the application of this similar paradigm for industrial objectives. Cellulase enzyme exhibits greater promise in many critical industries, including biofuel manufacture, textile smoothing and finishing, paper and pulp manufacturing, and farming. However, the study on cellulolytic enzymes must move forward in various directions, including increasing the activity of cellulase as well as designing peptides to give biocatalysts their desired attributes. This manuscript includes an overview of current research on different sources of cellulases, their production, and biochemical characterization.

Erythrocyte metabolism

Our aim is to present an updated overview of the erythrocyte metabolism highlighting its richness and complexity. We have manually collected and connected the available biochemical pathways and integrated them into a functional metabolic map. The focus of this map is on the main biochemical pathways consisting of glycolysis, the pentose phosphate pathway, redox metabolism, oxygen metabolism, purine/nucleoside metabolism, and membrane transport. Other recently emerging pathways are also curated, like the methionine salvage pathway, the glyoxalase system, carnitine metabolism, and the lands cycle, as well as remnants of the carboxylic acid metabolism. An additional goal of this review is to present the dynamics of erythrocyte metabolism, providing key numbers used to perform basic quantitative analyses. By synthesizing experimental and computational data, we conclude that glycolysis, pentose phosphate pathway, and redox metabolism are the foundations of erythrocyte metabolism. Additionally, the erythrocyte can sense oxygen levels and oxidative stress adjusting its mechanics, metabolism, and function. In conclusion, fine-tuning of erythrocyte metabolism controls one of the most important biological processes, that is, oxygen loading, transport, and delivery.

Metabolic Engineering: Methodologies and Applications

Metabolic engineering aims to improve the production of economically valuable molecules through the genetic manipulation of microbial metabolism. While the discipline is a little over 30 years old, advancements in metabolic engineering have given way to industrial-level molecule production benefitting multiple industries such as chemical, agriculture, food, pharmaceutical, and energy industries. This review describes the design, build, test, and learn steps necessary for leading a successful metabolic engineering campaign. Moreover, we highlight major applications of metabolic engineering, including synthesizing chemicals and fuels, broadening substrate utilization, and improving host robustness with a focus on specific case studies. Finally, we conclude with a discussion on perspectives and future challenges related to metabolic engineering.

Optimizing microbial networks through metabolic bypasses

Metabolism has long been considered as a relatively stiff set of biochemical reactions. This somewhat outdated and dogmatic view has been challenged over the last years, as multiple studies exposed unprecedented plasticity of metabolism by exploring rational and evolutionary modifications within the metabolic network of cell factories. Of particular importance is the emergence of metabolic bypasses, which consist of enzymatic reaction(s) that support unnatural connections between metabolic nodes. Such novel topologies can be generated through the introduction of heterologous enzymes or by upregulating native enzymes (sometimes relying on promiscuous activities thereof). Altogether, the adoption of bypasses resulted in an expansion in the capacity of the host's metabolic network, which can be harnessed for bioproduction. In this review, we discuss modifications to the canonical architecture of central carbon metabolism derived from such bypasses towards six optimization purposes: stoichiometric gain, overcoming kinetic limitations, solving thermodynamic barriers, circumventing toxic intermediates, uncoupling product synthesis from biomass formation, and altering redox cofactor specificity. The metabolic costs associated with bypass-implementation are likewise discussed, including tailoring their design towards improving bioproduction.

Animal Models of Dysregulated Cardiac Metabolism

As a muscular pump that contracts incessantly throughout life, the heart must constantly generate cellular energy to support contractile function and fuel ionic pumps to maintain electrical homeostasis. Thus, mitochondrial metabolism of multiple metabolic substrates such as fatty acids, glucose, ketones, and lactate is essential to ensuring an uninterrupted supply of ATP. Multiple metabolic pathways converge to maintain myocardial energy homeostasis. The regulation of these cardiac metabolic pathways has been intensely studied for many decades. Rapid adaptation of these pathways is essential for mediating the myocardial adaptation to stress, and dysregulation of these pathways contributes to myocardial pathophysiology as occurs in heart failure and in metabolic disorders such as diabetes. The regulation of these pathways reflects the complex interactions of cell-specific regulatory pathways, neurohumoral signals, and changes in substrate availability in the circulation. Significant advances have been made in the ability to study metabolic regulation in the heart, and animal models have played a central role in contributing to this knowledge. This review will summarize metabolic pathways in the heart and describe their contribution to maintaining myocardial contractile function in health and disease. The review will summarize lessons learned from animal models with altered systemic metabolism and those in which specific metabolic regulatory pathways have been genetically altered within the heart. The relationship between intrinsic and extrinsic regulators of cardiac metabolism and the pathophysiology of heart failure and how these have been informed by animal models will be discussed.

Predictive design of sigma factor-specific promoters

To engineer synthetic gene circuits, molecular building blocks are developed which can modulate gene expression without interference, mutually or with the host's cell machinery. As the complexity of gene circuits increases, automated design tools and tailored building blocks to ensure perfect tuning of all components in the network are required. Despite the efforts to develop prediction tools that allow forward engineering of promoter transcription initiation frequency (TIF), such a tool is still lacking. Here, we use promoter libraries of E. coli sigma factor 70 (σ70)- and B. subtilis σB-, σF- and σW-dependent promoters to construct prediction models, capable of both predicting promoter TIF and orthogonality of the σ-specific promoters. This is achieved by training a convolutional neural network with high-throughput DNA sequencing data from fluorescence-activated cell sorted promoter libraries. This model functions as the base of the online promoter design tool (ProD), providing tailored promoters for tailored genetic systems.

Enhancing Biosynthesis and Manipulating Flux in Whole Cells with Abiotic Catalysis

Metabolic engineering uses genetic strategies to drive flux through desired pathways. Recent work with electrochemical, photochemical, and chemocatalytic setups has revealed that these systems can also expand metabolic pathways and manipulate flux in whole cells. Electrochemical systems add or remove electrons from metabolic pathways to direct flux to more- or less-reduced products. Photochemical systems act as synthetic light-harvesting complexes and yield artificial photosynthetic organisms. Biocompatible chemocatalysis increases product scope, streamlines syntheses, and yields single-flask processes to deliver products that would be challenging to synthesize through biosynthetic means alone. Here, we exclusively highlight systems that combine abiotic systems with living whole cells, taking particular note of strategies that enable the merger of these typically disparate systems.

Dynamic Inventory of Intermediate Metabolites of Cyanobacteria in a Diurnal Cycle

Cyanobacteria are gaining importance both as hosts for photoautotrophic production of chemicals and as model systems for studies of diurnal lifestyle. The proteome and transcriptome of cyanobacteria have been closely examined under diurnal growth, whereas the downstream effects on the intermediary metabolism have not received sufficient attention. The present study focuses on identifying the cellular metabolites whose inventories undergo dramatic changes in a fast-growing cyanobacterium, Synechococcus elongatus PCC 11801. We identified and quantified 67 polar metabolites, whose inventory changes significantly during diurnal growth, with some metabolites changing by 100-fold. The Calvin-Benson-Bassham cycle intermediates peak at midday to support fast growth. The hitherto unexplored γ-glutamyl peptides act as reservoirs of amino acids. Interestingly, several storage molecules or their precursors accumulate during the dark phase, dispelling the notion that all biosynthetic activity takes place in the light phase. Our results will guide metabolic modeling and strain engineering of cyanobacteria.

•

We identify and quantify 67 polar intermediate metabolites in cyanobacteria via LC-MS

•

A number of metabolites show large variations during the diurnal cycle

•

Intermediates of the CBB cycle peak at midday, coinciding with peak in growth rate

•

Gamma-glutamyl dipeptides identified as new storage compounds that peak at dawn

Photosynthetic Co-Production of Succinate and Ethylene in A Fast-Growing Cyanobacterium, Synechococcus elongatus PCC 11801

Cyanobacteria are emerging as hosts for photoautotrophic production of chemicals. Recent studies have attempted to stretch the limits of photosynthetic production, typically focusing on one product at a time, possibly to minimise the additional burden of product separation. Here, we explore the simultaneous production of two products that can be easily separated: ethylene, a gaseous product, and succinate, an organic acid that accumulates in the culture medium. This was achieved by expressing a single copy of the ethylene forming enzyme (efe) under the control of P_cpcB, the inducer-free super-strong promoter of phycocyanin β subunit. We chose the recently reported, fast-growing and robust cyanobacterium, Synechococcus elongatus PCC 11801, as the host strain. A stable recombinant strain was constructed using CRISPR-Cpf1 in a first report of markerless genome editing of this cyanobacterium. Under photoautotrophic conditions, the recombinant strain shows specific productivities of 338.26 and 1044.18 μmole/g dry cell weight/h for ethylene and succinate, respectively. These results compare favourably with the reported productivities for individual products in cyanobacteria that are highly engineered. Metabolome profiling and ¹³C labelling studies indicate carbon flux redistribution and suggest avenues for further improvement. Our results show that S. elongatus PCC 11801 is a promising candidate for metabolic engineering.

The fitness challenge of studying molecular adaptation

Advances in bioinformatics and high-throughput genetic analysis increasingly allow us to predict the genetic basis of adaptive traits. These predictions can be tested and confirmed, but the molecular-level changes - i.e. the molecular adaptation - that link genetic differences to organism fitness remain generally unknown. In recent years, a series of studies have started to unpick the mechanisms of adaptation at the molecular level. In particular, this work has examined how changes in protein function, activity, and regulation cause improved organismal fitness. Key to addressing molecular adaptations is identifying systems and designing experiments that integrate changes in the genome, protein chemistry (molecular phenotype), and fitness. Knowledge of the molecular changes underpinning adaptations allow new insight into the constraints on, and repeatability of adaptations, and of the basis of non-additive interactions between adaptive mutations. Here we critically discuss a series of studies that examine the molecular-level adaptations that connect genetic changes and fitness.

Metabolic engineering of a fast-growing cyanobacterium Synechococcus elongatus PCC 11801 for photoautotrophic production of succinic acid

BACKGROUND

Cyanobacteria, a group of photosynthetic prokaryotes, are being increasingly explored for direct conversion of carbon dioxide to useful chemicals. However, efforts to engineer these photoautotrophs have resulted in low product titers. This may be ascribed to the bottlenecks in metabolic pathways, which need to be identified for rational engineering. We engineered the recently reported, fast-growing and robust cyanobacterium, Synechococcus elongatus PCC 11801 to produce succinate, an important platform chemical. Previously, engineering of the model cyanobacterium S. elongatus PCC 7942 has resulted in succinate titer of 0.43 g l^-1 in 8 days.

RESULTS

Building on the previous report, expression of α-ketoglutarate decarboxylase, succinate semialdehyde dehydrogenase and phosphoenolpyruvate carboxylase yielded a succinate titer of 0.6 g l^-1 in 5 days suggesting that PCC 11801 is better suited as host for production. Profiling of the engineered strains for 57 intermediate metabolites, a number of enzymes and qualitative analysis of key transcripts revealed potential flux control points. Based on this, we evaluated the effects of overexpression of sedoheptulose-1,7-bisphosphatase, citrate synthase and succinate transporters and knockout of succinate dehydrogenase and glycogen synthase A. The final construct with seven genes overexpressed and two genes knocked out resulted in photoautotrophic production of 0.93 g l^-1 succinate in 5 days.

CONCLUSION

While the fast-growing strain PCC 11801 yielded a much higher titer than the model strain, the efficient photoautotrophy of this novel isolate needs to be harnessed further for the production of desired chemicals. Engineered strains of S. elongatus PCC 11801 showed dramatic alterations in the levels of several metabolites suggesting far reaching effects of pathway engineering. Attempts to overexpress enzymes deemed to be flux controlling led to the emergence of other potential rate-limiting steps. Thus, this process of debottlenecking of the pathway needs to be repeated several times to obtain a significantly superior succinate titer.

Investigation of the methylerythritol 4-phosphate pathway for microbial terpenoid production through metabolic control analysis

BACKGROUND

Terpenoids are of high interest as chemical building blocks and pharmaceuticals. In microbes, terpenoids can be synthesized via the methylerythritol phosphate (MEP) or mevalonate (MVA) pathways. Although the MEP pathway has a higher theoretical yield, metabolic engineering has met with little success because the regulation of the pathway is poorly understood.

RESULTS

We applied metabolic control analysis to the MEP pathway in Escherichia coli expressing a heterologous isoprene synthase gene (ispS). The expression of ispS led to the accumulation of isopentenyl pyrophosphate (IPP)/dimethylallyl pyrophosphate (DMAPP) and severely impaired bacterial growth, but the coexpression of ispS and isopentenyl diphosphate isomerase (idi) restored normal growth and wild-type IPP/DMAPP levels. Targeted proteomics and metabolomics analysis provided a quantitative description of the pathway, which was perturbed by randomizing the ribosome binding site in the gene encoding 1-deoxyxylulose 5-phosphate synthase (Dxs). Dxs has a flux control coefficient of 0.35 (i.e., a 1% increase in Dxs activity resulted in a 0.35% increase in pathway flux) in the isoprene-producing strain and therefore exerted significant control over the flux though the MEP pathway. At higher dxs expression levels, the intracellular concentration of 2-C-methyl-D-erythritol-2,4-cyclopyrophosphate (MEcPP) increased substantially in contrast to the other MEP pathway intermediates, which were linearly dependent on the abundance of Dxs. This indicates that 4-hydroxy-3-methylbut-2-en-1-yl diphosphate synthase (IspG), which consumes MEcPP, became saturated and therefore limited the flux towards isoprene. The higher intracellular concentrations of MEcPP led to the efflux of this intermediate into the growth medium.

DISCUSSION

These findings show the importance of Dxs, Idi and IspG and metabolite export for metabolic engineering of the MEP pathway and will facilitate further approaches for the microbial production of valuable isoprenoids.

Advances in the Metabolic Engineering of Escherichia coli for the Manufacture of Monoterpenes

Monoterpenes are commonly applied as pharmaceuticals and valuable chemicals in various areas. The bioproduction of valuable monoterpenes in prokaryotic microbial hosts, such as E. coli, has progressed considerably thanks to the development of different outstanding approaches. However, the large-scale production of monoterpenes still presents considerable limitations. Thus, process development warrants further investigations. This review discusses the endogenous methylerythritol-4-phosphate-dependent pathway engineering and the exogenous mevalonate-dependent isoprenoid pathway introduction, as well as the accompanied optimization of rate-limiting enzymes, metabolic flux, and product toxicity tolerance. We suggest further studies to focus on the development of systematical, integrational, and synthetic biological strategies in light of the inter disciplines at the cutting edge. Our review provides insights into the current advances of monoterpene bioengineering and serves as a reference for future studies to promote the industrial production of valuable monoterpenes.

The calculation of transcript flux ratios reveals single regulatory mechanisms capable of activation and repression

The regulation of transcription allows cells to adjust the rate of RNA polymerases (RNAPs) initiated in a promoter-specific manner. Classically, transcription factors are directed to a subset of promoters via the recognition of DNA sequence motifs. However, a unique class of regulators is recruited directly through interactions with RNAP. Surprisingly, these factors may still possess promoter specificity, and it has been postulated that the same kinetic mechanism leads to different regulatory outcomes depending on a promoter's basal rate constants. However, mechanistic studies of regulation typically report factor activity in terms of changes in the thermodynamics or kinetics of individual steps or states while qualitatively linking these observations to measured changes in transcript production. Here, I present online calculators that allow for the direct testing of mechanistic hypotheses by calculating the steady-state transcript flux in the presence and absence of a factor as a function of initiation rate constants. By evaluating how the flux ratio of a single kinetic mechanism varies across promoter space, quantitative insights into the potential of a mechanism to generate promoter-specific regulatory outcomes are obtained. Using these calculations, I predict that the mycobacterial transcription factor CarD is capable of repression in addition to its known role as an activator of ribosomal genes. In addition, a modification of the mechanism of the stringent response factors DksA/guanosine 5'-diphosphate 3'-diphosphate (ppGpp) is proposed based on their ability to differentially regulate transcription across promoter space. Overall, I conclude that a multifaceted kinetic mechanism is a requirement for differential regulation by this class of factors.

Final grain weight is not limited by the activity of key starch-synthesising enzymes during grain filling in wheat

Since starch is by far the major component of the mature wheat grain, it has been assumed that variation in the capacity for starch synthesis during grain filling can influence final grain weight. We investigated this assumption by studying a total of 54 wheat genotypes including elite varieties and landraces that were grown in two successive years in fields in the east of England. The weight, water content, sugars, starch, and maximum catalytic activities of two enzymes of starch biosynthesis, ADP-glucose pyrophosphorylase and soluble starch synthase, were measured during grain filling. The relationships between these variables and the weights and starch contents of mature grains were analysed. Final grain weight showed few or no significant correlations with enzyme activities, sugar levels, or starch content during grain filling, or with starch content at maturity. We conclude that neither sugar availability nor enzymatic capacity for starch synthesis during grain filling significantly influenced final grain weight in our field conditions. We suggest that final grain weight may be largely determined by developmental processes prior to grain filling. Starch accumulation then fills the grain to a physical limit set by developmental processes. This conclusion is in accord with those from previous studies in which source or sink strength has been artificially manipulated.

A metabolic control analysis approach to introduce the study of systems in biochemistry: the glycolytic pathway in the red blood cell

Metabolic control analysis (MCA) is a promising approach in biochemistry aimed at understanding processes in a quantitative fashion. Here the contribution of enzymes and transporters to the control of a given pathway flux and metabolite concentrations is determined and expressed quantitatively by means of numerical coefficients. Metabolic flux can be influenced by a wide variety of modulators acting on one or more metabolic steps along the pathway. We describe a laboratory exercise to study metabolic regulation of human erythrocytes (RBCs). Within the framework of MCA, students use these cells to determine the sensitivity of the glycolytic flux to two inhibitors (iodoacetic acid: IA, and iodoacetamide: IAA) known to act on the enzyme glyceraldehyde-3-phosphate-dehydrogenase. Glycolytic flux was estimated by determining the concentration of extracellular lactate, the end product of RBC glycolysis. A low-cost colorimetric assay was implemented, that takes advantage of the straightforward quantification of the absorbance signal from the photographic image of the multi-well plate taken with a standard digital camera. Students estimate flux response coefficients for each inhibitor by fitting an empirical function to the experimental data, followed by analytical derivation of this function. IA and IAA exhibit qualitatively different patterns, which are thoroughly analyzed in terms of the physicochemical properties influencing their action on the target enzyme. IA causes highest glycolytic flux inhibition at lower concentration than IAA. This work illustrates the feasibility of using the MCA approach to study key variables of a simple metabolic system, in the context of an upper level biochemistry course. © 2018 International Union of Biochemistry and Molecular Biology, 46(5):502-515, 2018.

Four Key Steps Control Glycolytic Flux in Mammalian Cells

Altered glycolysis is a hallmark of diseases including diabetes and cancer. Despite intensive study of the contributions of individual glycolytic enzymes, systems-level analyses of flux control through glycolysis remain limited. Here, we overexpress in two mammalian cell lines the individual enzymes catalyzing each of the 12 steps linking extracellular glucose to excreted lactate, and find substantial flux control at four steps: glucose import, hexokinase, phosphofructokinase, and lactate export (and not at any steps of lower glycolysis). The four flux-controlling steps are specifically upregulated by the Ras oncogene: optogenetic Ras activation rapidly induces the transcription of isozymes catalyzing these four steps and enhances glycolysis. At least one isozyme catalyzing each of these four steps is consistently elevated in human tumors. Thus, in the studied contexts, flux control in glycolysis is concentrated in four key enzymatic steps. Upregulation of these steps in tumors likely underlies the Warburg effect.

Understanding the impact of the cofactor swapping of isocitrate dehydrogenase over the growth phenotype of Escherichia coli on acetate by using constraint-based modeling

It has been proposed that NADP⁺-specificity of isocitrate dehydrogenase (ICDH) evolved as an adaptation of microorganisms to grow on acetate as the sole source of carbon and energy. In Escherichia coli, changing the cofactor specificity of ICDH from NADP⁺ to NAD⁺ (cofactor swapping) decreases the growth rate on acetate. However, the metabolic basis of this phenotype has not been analyzed. In this work, we used constraint-based modeling to investigate the effect of the cofactor swapping of ICDH in terms of energy production, response of alternative sources of NADPH, and partitioning of fluxes between ICDH and isocitrate lyase (ICL) -a crucial bifurcation when the bacterium grows on acetate-. We generated E. coli strains expressing NAD⁺-specific ICDH instead of the native enzyme, and bearing the deletion of the NADPH-producing transhydrogenase PntAB. We measured their growth rate and acetate uptake rate, modeled the distribution of metabolic fluxes by Flux Balance Analysis (FBA), and quantified the specific activities of NADPH-producing dehydrogenases in central pathways. The cofactor swapping of ICDH led to one-third decrease in biomass yield, irrespective of the presence of PntAB. According to our simulations, the diminution in growth rate observed upon cofactor swapping could be explained by one-half decrease in the total production of NADPH and a lower availability of carbon for biosynthesis because of a change in the partition at the isocitrate bifurcation. Together with an increased total ATP production, this scenario resulted in a 10-fold increment in the flux of ATP not used for growing purposes. PntAB was identified as the primary NADPH balancing response, with the dehydrogenases of the oxidative branch of the Pentose Phosphate Pathway and the malic enzyme playing a role in its absence. We propose that in the context of E. coli growing on acetate, the NADP⁺-specificity of ICDH is a trait that impacts not only NADPH production, but also the efficient allocation of carbon and energy.

Competitive resource allocation to metabolic pathways contributes to overflow metabolisms and emergent properties in cross-feeding microbial consortia

Resource scarcity is a common stress in nature and has a major impact on microbial physiology. This review highlights microbial acclimations to resource scarcity, focusing on resource investment strategies for chemoheterotrophs from the molecular level to the pathway level. Competitive resource allocation strategies often lead to a phenotype known as overflow metabolism; the resulting overflow byproducts can stabilize cooperative interactions in microbial communities and can lead to cross-feeding consortia. These consortia can exhibit emergent properties such as enhanced resource usage and biomass productivity. The literature distilled here draws parallels between in silico and laboratory studies and ties them together with ecological theories to better understand microbial stress responses and mutualistic consortia functioning.

An Automated Pipeline for Engineering Many-Enzyme Pathways: Computational Sequence Design, Pathway Expression-Flux Mapping, and Scalable Pathway Optimization

Engineering many-enzyme metabolic pathways suffers from the design curse of dimensionality. There are an astronomical number of synonymous DNA sequence choices, though relatively few will express an evolutionary robust, maximally productive pathway without metabolic bottlenecks. To solve this challenge, we have developed an integrated, automated computational-experimental pipeline that identifies a pathway's optimal DNA sequence without high-throughput screening or many cycles of design-build-test. The first step applies our Operon Calculator algorithm to design a host-specific evolutionary robust bacterial operon sequence with maximally tunable enzyme expression levels. The second step applies our RBS Library Calculator algorithm to systematically vary enzyme expression levels with the smallest-sized library. After characterizing a small number of constructed pathway variants, measurements are supplied to our Pathway Map Calculator algorithm, which then parameterizes a kinetic metabolic model that ultimately predicts the pathway's optimal enzyme expression levels and DNA sequences. Altogether, our algorithms provide the ability to efficiently map the pathway's sequence-expression-activity space and predict DNA sequences with desired metabolic fluxes. Here, we provide a step-by-step guide to applying the Pathway Optimization Pipeline on a desired multi-enzyme pathway in a bacterial host.

On the translocation of bacteria and their lipopolysaccharides between blood and peripheral locations in chronic, inflammatory diseases: the central roles of LPS and LPS-induced cell death

We have recently highlighted (and added to) the considerable evidence that blood can contain dormant bacteria. By definition, such bacteria may be resuscitated (and thus proliferate). This may occur under conditions that lead to or exacerbate chronic, inflammatory diseases that are normally considered to lack a microbial component. Bacterial cell wall components, such as the endotoxin lipopolysaccharide (LPS) of Gram-negative strains, are well known as potent inflammatory agents, but should normally be cleared. Thus, their continuing production and replenishment from dormant bacterial reservoirs provides an easy explanation for the continuing, low-grade inflammation (and inflammatory cytokine production) that is characteristic of many such diseases. Although experimental conditions and determinants have varied considerably between investigators, we summarise the evidence that in a great many circumstances LPS can play a central role in all of these processes, including in particular cell death processes that permit translocation between the gut, blood and other tissues. Such localised cell death processes might also contribute strongly to the specific diseases of interest. The bacterial requirement for free iron explains the strong co-existence in these diseases of iron dysregulation, LPS production, and inflammation. Overall this analysis provides an integrative picture, with significant predictive power, that is able to link these processes via the centrality of a dormant blood microbiome that can resuscitate and shed cell wall components.

Construction of feasible and accurate kinetic models of metabolism: A Bayesian approach

Kinetic models are essential to quantitatively understand and predict the behaviour of metabolic networks. Detailed and thermodynamically feasible kinetic models of metabolism are inherently difficult to formulate and fit. They have a large number of heterogeneous parameters, are non-linear and have complex interactions. Many powerful fitting strategies are ruled out by the intractability of the likelihood function. Here, we have developed a computational framework capable of fitting feasible and accurate kinetic models using Approximate Bayesian Computation. This framework readily supports advanced modelling features such as model selection and model-based experimental design. We illustrate this approach on the tightly-regulated mammalian methionine cycle. Sampling from the posterior distribution, the proposed framework generated thermodynamically feasible parameter samples that converged on the true values, and displayed remarkable prediction accuracy in several validation tests. Furthermore, a posteriori analysis of the parameter distributions enabled appraisal of the systems properties of the network (e.g., control structure) and key metabolic regulations. Finally, the framework was used to predict missing allosteric interactions.

Reporter pathway analysis from transcriptome data: Metabolite-centric versus Reaction-centric approach

A systems-based investigation of the effect of perturbations on metabolic machinery is crucial to elucidate the mechanism behind perturbations. One way to investigate the perturbation-induced changes within the cell metabolism is to focus on pathway-level effects. In this study, three different perturbation types (genetic, environmental and disease-based) are analyzed to compute a list of reporter pathways, metabolic pathways which are significantly affected from a perturbation. The most common omics data type, transcriptome, is used as an input to the bioinformatic analysis. The pathways are scored by two alternative approaches: by averaging the changes in the expression levels of the genes controlling the associated reactions (reaction-centric), and by averaging the changes in the associated metabolites which were scored based on the associated genes (metabolite-centric). The analysis reveals the superiority of the novel metabolite-centric approach over the commonly used reaction-centric approach since it is based on metabolites which better represent the cross-talk among different pathways, enabling a more global and realistic cataloguing of network-wide perturbation effects.

Tracking the metabolic pulse of plant lipid production with isotopic labeling and flux analyses: Past, present and future

Metabolism is comprised of networks of chemical transformations, organized into integrated biochemical pathways that are the basis of cellular operation, and function to sustain life. Metabolism, and thus life, is not static. The rate of metabolites transitioning through biochemical pathways (i.e., flux) determines cellular phenotypes, and is constantly changing in response to genetic or environmental perturbations. Each change evokes a response in metabolic pathway flow, and the quantification of fluxes under varied conditions helps to elucidate major and minor routes, and regulatory aspects of metabolism. To measure fluxes requires experimental methods that assess the movements and transformations of metabolites without creating artifacts. Isotopic labeling fills this role and is a long-standing experimental approach to identify pathways and quantify their metabolic relevance in different tissues or under different conditions. The application of labeling techniques to plant science is however far from reaching it potential. In light of advances in genetics and molecular biology that provide a means to alter metabolism, and given recent improvements in instrumentation, computational tools and available isotopes, the use of isotopic labeling to probe metabolism is becoming more and more powerful. We review the principal analytical methods for isotopic labeling with a focus on seminal studies of pathways and fluxes in lipid metabolism and carbon partitioning through central metabolism. Central carbon metabolic steps are directly linked to lipid production by serving to generate the precursors for fatty acid biosynthesis and lipid assembly. Additionally some of the ideas for labeling techniques that may be most applicable for lipid metabolism in the future were originally developed to investigate other aspects of central metabolism. We conclude by describing recent advances that will play an important future role in quantifying flux and metabolic operation in plant tissues.

Stirring rate regulates the proliferation and metabolism of microencapsulated recombinant CHO cells

Stirred tank bioreactors are the most widely used method for the large-scale culture of mammalian cells. However, the scale of stirred tank bioreactors is limited by insufficient oxygen/nutrient mixing and the accumulation of waste products in high cell density cultures. The most effective method to solve these problems is to increase the stirring rate; this usually leads to increased cell proliferation, but can decrease the utilization of nutrients for recombinant protein synthesis. To investigate the effects of stirring rate on the proliferation, metabolism, and recombinant protein yield of microencapsulated recombinant Chinese hamster ovary (rCHO) cells, the cells were cultured under different stirring rates, and cell viability, metabolic activity, and protein yield were measured. Microencapsulation promoted Desmodus rotundus salivary plasminogen activator expression, and higher stirring rates promoted increases in microencapsulated cell density and metabolic activity. However, the maximum yield of recombinant protein was obtained at a moderate stirring rate, whereas protein yield was decreased at the highest tested stirring rate. The stirring rate had a significant impact on the growth and protein expression of microencapsulated rCHO cells, and a specific stirring rate was identified to maximize the yield of recombinant protein.

Less is more: minimal expression of myoendothelial gap junctions optimizes cell-cell communication in virtual arterioles

Dysfunctional electrical signalling within the arteriolar wall is a major cause of cardiovascular disease. The endothelial cell layer constitutes the primary electrical pathway, co-ordinating contraction of the overlying smooth muscle cell (SMC) layer. As myoendothelial gap junctions (MEGJs) provide direct contact between the cell layers, proper vasomotor responses are thought to depend on a high, uniform MEGJ density. However, MEGJs are observed to be expressed heterogeneously within and among vascular beds. This discrepancy is addressed in the present study. As no direct measures of MEGJ conductance exist, we employed a computational modelling approach to vary the number, conductance and distribution of MEGJs. Our simulations demonstrate that a minimal number of randomly distributed MEGJs augment arteriolar cell-cell communication by increasing conduction efficiency and ensuring appropriate membrane potential responses in SMCs. We show that electrical coupling between SMCs must be tailored to the particular MEGJ distribution. Finally, observation of non-decaying mechanical conduction in arterioles without regeneration has been a long-standing controversy in the microvascular field. As heterogeneous MEGJ distributions provide for different conduction profiles along the cell layers, we demonstrate that a non-decaying conduction profile is possible in the SMC layer of a vessel with passive electrical properties. These intriguing findings redefine the concept of efficient electrical communication in the microcirculation, illustrating how heterogeneous properties, ubiquitous in biological systems, may have a profound impact on system behaviour and how acute local and global flow control is explained from the biophysical foundations.

Model based engineering of Pichia pastoris central metabolism enhances recombinant protein production

The production of recombinant proteins is frequently enhanced at the levels of transcription, codon usage, protein folding and secretion. Overproduction of heterologous proteins, however, also directly affects the primary metabolism of the producing cells. By incorporation of the production of a heterologous protein into a genome scale metabolic model of the yeast Pichia pastoris, the effects of overproduction were simulated and gene targets for deletion or overexpression for enhanced productivity were predicted. Overexpression targets were localized in the pentose phosphate pathway and the TCA cycle, while knockout targets were found in several branch points of glycolysis. Five out of 9 tested targets led to an enhanced production of cytosolic human superoxide dismutase (hSOD). Expression of bacterial β-glucuronidase could be enhanced as well by most of the same genetic modifications. Beneficial mutations were mainly related to reduction of the NADP/H pool and the deletion of fermentative pathways. Overexpression of the hSOD gene itself had a strong impact on intracellular fluxes, most of which changed in the same direction as predicted by the model. In vivo fluxes changed in the same direction as predicted to improve hSOD production. Genome scale metabolic modeling is shown to predict overexpression and deletion mutants which enhance recombinant protein production with high accuracy.

•

Recombinant protein production in P. pastoris affects the central metabolism.

•

A genome scale metabolic model can predict these metabolic flux changes.

•

Mutations in central metabolic genes enhanced recombinant protein yield up to 40%.

•

These beneficial mutations were predicted by the metabolic model with high accuracy.

Model of tryptophan metabolism, readily scalable using tissue-specific gene expression data

Tryptophan is utilized in various metabolic routes including protein synthesis, serotonin, and melatonin synthesis and the kynurenine pathway. Perturbations in these pathways have been associated with neurodegenerative diseases and cancer. Here we present a comprehensive kinetic model of the complex network of human tryptophan metabolism based upon existing kinetic data for all enzymatic conversions and transporters. By integrating tissue-specific expression data, modeling tryptophan metabolism in liver and brain returned intermediate metabolite concentrations in the physiological range. Sensitivity and metabolic control analyses identified expected key enzymes to govern fluxes in the branches of the network. Combining tissue-specific models revealed a considerable impact of the kynurenine pathway in liver on the concentrations of neuroactive derivatives in the brain. Moreover, using expression data from a cancer study predicted metabolite changes that resembled the experimental observations. We conclude that the combination of the kinetic model with expression data represents a powerful diagnostic tool to predict alterations in tryptophan metabolism. The model is readily scalable to include more tissues, thereby enabling assessment of organismal tryptophan metabolism in health and disease.

Structure and dynamics of molecular networks: a novel paradigm of drug discovery: a comprehensive review

Despite considerable progress in genome- and proteome-based high-throughput screening methods and in rational drug design, the increase in approved drugs in the past decade did not match the increase of drug development costs. Network description and analysis not only give a systems-level understanding of drug action and disease complexity, but can also help to improve the efficiency of drug design. We give a comprehensive assessment of the analytical tools of network topology and dynamics. The state-of-the-art use of chemical similarity, protein structure, protein-protein interaction, signaling, genetic interaction and metabolic networks in the discovery of drug targets is summarized. We propose that network targeting follows two basic strategies. The "central hit strategy" selectively targets central nodes/edges of the flexible networks of infectious agents or cancer cells to kill them. The "network influence strategy" works against other diseases, where an efficient reconfiguration of rigid networks needs to be achieved by targeting the neighbors of central nodes/edges. It is shown how network techniques can help in the identification of single-target, edgetic, multi-target and allo-network drug target candidates. We review the recent boom in network methods helping hit identification, lead selection optimizing drug efficacy, as well as minimizing side-effects and drug toxicity. Successful network-based drug development strategies are shown through the examples of infections, cancer, metabolic diseases, neurodegenerative diseases and aging. Summarizing >1200 references we suggest an optimized protocol of network-aided drug development, and provide a list of systems-level hallmarks of drug quality. Finally, we highlight network-related drug development trends helping to achieve these hallmarks by a cohesive, global approach.

Recent advances in technology supporting biopharmaceutical production from mammalian cells

The demand for production of glycoproteins from mammalian cell culture continues with an increased number of approvals as biopharmaceuticals for the treatment of unmet medical needs. This is particularly the case for humanized monoclonal antibodies which are the largest and fastest growing class of therapeutic pharmaceuticals. This demand has fostered efforts to improve the efficiency of production as well as to address the quality of the final product. Chinese hamster ovary cells are the predominant hosts for stable transfection and high efficiency production on a large scale. Specific productivity of recombinant glycoproteins from these cells can be expected to be above 50 pg/cell/day giving rise to culture systems with titers of around 5 g/L if appropriate fed-batch systems are employed. Cell engineering can delay the onset of programmed cell death to ensure prolonged maintenance of productive viable cells. The clinical efficacy and quality of the final product can be improved by strategic metabolic engineering. The best example of this is the targeted production of afucosylated antibodies with enhanced antibody-dependent cell cytotoxicity, an important function for use in cancer therapies. The development of culture media from non-animal sources continues and is important to ensure products of consistent quality and without the potential danger of contamination. Process efficiencies may also be improved by employing disposable bioreactors with the associated minimization of downtime. Finally, advances in downstream processing are needed to handle the increased supply of product from the bioreactor but maintaining the high purity demanded of these biopharmaceuticals.

Reprogramming of gene expression during compression wood formation in pine: coordinated modulation of S-adenosylmethionine, lignin and lignan related genes

BACKGROUND

Transcript profiling of differentiating secondary xylem has allowed us to draw a general picture of the genes involved in wood formation. However, our knowledge is still limited about the regulatory mechanisms that coordinate and modulate the different pathways providing substrates during xylogenesis. The development of compression wood in conifers constitutes an exceptional model for these studies. Although differential expression of a few genes in differentiating compression wood compared to normal or opposite wood has been reported, the broad range of features that distinguish this reaction wood suggest that the expression of a larger set of genes would be modified.

RESULTS

By combining the construction of different cDNA libraries with microarray analyses we have identified a total of 496 genes in maritime pine (Pinus pinaster, Ait.) that change in expression during differentiation of compression wood (331 up-regulated and 165 down-regulated compared to opposite wood). Samples from different provenances collected in different years and geographic locations were integrated into the analyses to mitigate the effects of multiple sources of variability. This strategy allowed us to define a group of genes that are consistently associated with compression wood formation. Correlating with the deposition of a thicker secondary cell wall that characterizes compression wood development, the expression of a number of genes involved in synthesis of cellulose, hemicellulose, lignin and lignans was up-regulated. Further analysis of a set of these genes involved in S-adenosylmethionine metabolism, ammonium recycling, and lignin and lignans biosynthesis showed changes in expression levels in parallel to the levels of lignin accumulation in cells undergoing xylogenesis in vivo and in vitro.

CONCLUSIONS

The comparative transcriptomic analysis reported here have revealed a broad spectrum of coordinated transcriptional modulation of genes involved in biosynthesis of different cell wall polymers associated with within-tree variations in pine wood structure and composition. In particular, we demonstrate the coordinated modulation at transcriptional level of a gene set involved in S-adenosylmethionine synthesis and ammonium assimilation with increased demand for coniferyl alcohol for lignin and lignan synthesis, enabling a better understanding of the metabolic requirements in cells undergoing lignification.

Metabolic adaptation of MDCK cells to different growth conditions: effects on catalytic activities of central metabolic enzymes

Lactate and ammonia are the most important waste products of central carbon metabolism in mammalian cell cultures. In particular during batch and fed-batch cultivations these toxic by-products are excreted into the medium in large amounts, and not only affect cell viability and productivity but often also prevent growth to high cell densities. The most promising approach to overcome such a metabolic imbalance is the replacement of one or several components in the culture medium. It has been previously shown that pyruvate can be substituted for glutamine in cultures of adherent Madin-Darby canine kidney (MDCK) cells. As a consequence, the cells not only released no ammonia but glucose consumption and lactate production were also reduced significantly. In this work, the impact of media changes on glucose and glutamine metabolism was further elucidated by using a high-throughput platform for enzyme activity measurements of mammalian cells. Adherent MDCK cells were grown to stationary and exponential phase in six-well plates in serum-containing GMEM supplemented with glutamine or pyruvate. A total number of 28 key metabolic enzyme activities of cell extracts were analyzed. The overall activity of the pentose phosphate pathway was up-regulated during exponential cell growth in pyruvate-containing medium suggesting that more glucose-6-phosphate was channeled into the oxidative branch. Furthermore, the anaplerotic enzymes pyruvate carboxylase and pyruvate dehydrogenase showed higher cell specific activities with pyruvate. An increase in cell specific activity was also found for NAD(+)-dependent isocitrate dehydrogenase, glutamate dehydrogenase, and glutamine synthetase in MDCK cells grown with pyruvate. It can be assumed that the increase in enzyme activities was required to compensate for the energy demand and to replenish the glutamine pool. On the other hand, the activities of glutaminolytic enzymes (e.g., alanine and aspartate transaminase) were decreased in cells grown with pyruvate, which seems to be related to a decreased glutamine metabolism.

The principle of sufficiency and the evolution of control: using control analysis to understand the design principles of biological systems

Control analysis can be used to try to understand why (quantitatively) systems are the way that they are, from rate constants within proteins to the relative amount of different tissues in organisms. Many biological parameters appear to be optimized to maximize rates under the constraint of minimizing space utilization. For any biological process with multiple steps that compete for control in series, evolution by natural selection will tend to even out the control exerted by each step. This is for two reasons: (i) shared control maximizes the flux for minimum protein concentration, and (ii) the selection pressure on any step is proportional to its control, and selection will, by increasing the rate of a step (relative to other steps), decrease its control over a pathway. The control coefficient of a parameter P over fitness can be defined as (∂N/N)/(∂P/P), where N is the number of individuals in the population, and ∂N is the change in that number as a result of the change in P. This control coefficient is equal to the selection pressure on P. I argue that biological systems optimized by natural selection will conform to a principle of sufficiency, such that the control coefficient of all parameters over fitness is 0. Thus in an optimized system small changes in parameters will have a negligible effect on fitness. This principle naturally leads to (and is supported by) the dominance of wild-type alleles over null mutants.

Common phenotype of resting mouse extensor digitorum longus and soleus muscles: equal ATPase and glycolytic flux during transient anoxia

Rates of ATPase and glycolysis are several times faster in actively contracting mouse extensor digitorum longus muscle (EDL) than soleus (SOL), but we find these rates are not distinguishable at rest. We used a transient anoxic perturbation of steady state energy balance to decrease phosphocreatine (PCr) reversibly and to measure the rates of ATPase and of lactate production without muscle activation or contraction. The rate of glycolytic ATP synthesis is less than the ATPase rate, accounting for the continual PCr decrease during anoxia in both muscles. We fitted a mathematical model validated with properties of enzymes and solutes measured in vitro and appropriate for the transient perturbation of these muscles to experimental data to test whether the model accounts for the results. Simulations showed equal rates of ATPase and lactate production in both muscles. ATPase controls glycolytic flux by feedback from its products. Adenylate kinase function is critical because a rise in [AMP] is necessary to activate glycogen phosphorylase. ATPase is the primary source of H+ production. The sum of contributions of the 13 reactions of the glycogenolytic and glycolytic network to total proton load is negligible. The stoichiometry of lactate and H+ production is near unity. These results identify a default state of energy metabolism for resting muscle in which there is no difference in the metabolic phenotype of EDL and SOL. Therefore, additional control mechanisms, involving higher ATPase flux and [Ca2+], must exist to explain the well-known difference in glycolytic rates in fast-twitch and slow-twitch muscles in actively contracting muscle.

Sulphur flux through the sulphate assimilation pathway is differently controlled by adenosine 5'-phosphosulphate reductase under stress and in transgenic poplar plants overexpressing gamma-ECS, SO, or APR

Sulphate assimilation provides reduced sulphur for the synthesis of cysteine, methionine, and numerous other essential metabolites and secondary compounds. The key step in the pathway is the reduction of activated sulphate, adenosine 5'-phosphosulphate (APS), to sulphite catalysed by APS reductase (APR). In the present study, [(35)S]sulphur flux from external sulphate into glutathione (GSH) and proteins was analysed to check whether APR controls the flux through the sulphate assimilation pathway in poplar roots under some stress conditions and in transgenic poplars. (i) O-Acetylserine (OAS) induced APR activity and the sulphur flux into GSH. (ii) The herbicide Acetochlor induced APR activity and results in a decline of GSH. Thereby the sulphur flux into GSH or protein remained unaffected. (iii) Cd treatment increased APR activity without any changes in sulphur flux but lowered sulphate uptake. Several transgenic poplar plants that were manipulated in sulphur metabolism were also analysed. (i) Transgenic poplar plants that overexpressed the gamma-glutamylcysteine synthetase (gamma-ECS) gene, the enzyme catalysing the key step in GSH formation, showed an increase in sulphur flux into GSH and sulphate uptake when gamma-ECS was targeted to the cytosol, while no changes in sulphur flux were observed when gamma-ECS was targeted to plastids. (ii) No effect on sulphur flux was observed when the sulphite oxidase (SO) gene from Arabidopsis thaliana, which catalyses the back reaction of APR, that is the reaction from sulphite to sulphate, was overexpressed. (iii) When Lemna minor APR was overexpressed in poplar, APR activity increased as expected, but no changes in sulphur flux were observed. For all of these experiments the flux control coefficient for APR was calculated. APR as a controlling step in sulphate assimilation seems obvious under OAS treatment, in gamma-ECS and SO overexpressing poplars. A possible loss of control under certain conditions, that is Cd treatment, Acetochlor treatment, and in APR overexpressing poplar, is discussed.

Metabolic flux analysis in plants: coping with complexity

Theory and experience in metabolic engineering both show that metabolism operates at the network level. In plants, this complexity is compounded by a high degree of compartmentation and the synthesis of a very wide array of secondary metabolic products. A further challenge to understanding and predicting plant metabolic function is posed by our ignorance about the structure of metabolic networks even in well-studied systems. Metabolic flux analysis (MFA) provides tools to measure and model the functioning of metabolism, and is making significant contributions to coping with their complexity. This review gives an overview of different MFA approaches, the measurements required to implement them and the information they yield. The application of MFA methods to plant systems is then illustrated by several examples from the recent literature. Next, the challenges that plant metabolism poses for MFA are discussed together with ways that these can be addressed. Lastly, new developments in MFA are described that can be expected to improve the range and reliability of plant MFA in the coming years.

In silico strategy to rationally engineer metabolite production: A case study for threonine in Escherichia coli

Genetic engineering of metabolic pathways is a standard strategy to increase the production of metabolites of economic interest. However, such flux increases could very likely lead to undesirable changes in metabolite concentrations, producing deleterious perturbations on other cellular processes. These negative effects could be avoided by implementing a balanced increase of enzyme concentrations according to the Universal Method [Kacser and Acerenza (1993) Eur J Biochem 216:361-367]. Exact application of the method usually requires modification of many reactions, which is difficult to achieve in practice. Here, improvement of threonine production via pyruvate kinase deletion in Escherichia coli is used as a case study to demonstrate a partial application of the Universal Method, which includes performing sensitivity analysis. Our analysis predicts that manipulating a few reactions is sufficient to obtain an important increase in threonine production without major perturbations of metabolite concentrations.

Rethinking metabolic control

Modulation of metabolic fluxes in plants is usually not a successful business. The main reason is our limited understanding of metabolic plasticity and metabolic control, with the latter still largely influenced by the idea that each pathway has a rate limiting step controlling the flux. Not only is experimental evidence for such steps lacking for most pathways, despite intensive search, but there are also theoretical arguments against the idea that highly regulated enzymes catalyzing reactions far from equilibrium must be considered a priori rate limiting. Conversely, it is argued that reactions close to equilibrium need a lot of enzyme to be maintained close to equilibrium and, contrary to accepted wisdom, begin to limit flux when reduced. Using a few key examples of plant metabolic pathways as case studies, I draw some general conclusions. The approach of augmenting flux by pushing a pathway from above is well exemplified by the attempts at increasing starch content in potato tubers, where several different approaches failed. Also pulling at the other end (close to the end product) has yielded little improvement, while targeting a reaction close to equilibrium (ADP/ATP translocation at the plastid envelope) successfully increased starch content. Rethinking control is equally well applicable to photosynthesis, with prime examples of 'neglected', unregulated enzymes exerting significant control and overprized 'limiting' enzymes having little control in normal conditions like rubisco. In this new paradigm, the role of most control mechanisms is also challenged: feedback inhibition and post-translational modification of enzymes are relevant to metabolite homeostasis rather than flux control, with moiety conservation being a major reason for this constraint. I advocate a more extensive use of control circuitry elements (e.g. sensors like riboswitches), metabolic shortcuts and transcription factors in metabolic engineering.

Super life--how and why 'cell selection' leads to the fastest-growing eukaryote

What is the highest possible replication rate for living organisms? The cellular growth rate is controlled by a variety of processes. Therefore, it is unclear which metabolic process or group of processes should be activated to increase growth rate. An organism that is already growing fast may already have optimized through evolution all processes that could be optimized readily, but may be confronted with a more generic limitation. Here we introduce a method called 'cell selection' to select for highest growth rate, and show how such a cellular site of 'growth control' was identified. By applying pH-auxostat cultivation to the already fast-growing yeast Kluyveromyces marxianus for a sufficiently long time, we selected a strain with a 30% increased growth rate; its cell-cycle time decreased to 52 min, much below that reported to date for any eukaryote. The increase in growth rate was accompanied by a 40% increase in cell surface at a fairly constant cell volume. We show how the increase in growth rate can be explained by a dominant (80%) limitation of growth by the group of membrane processes (a 0.7% increase of specific growth rate to a 1% increase in membrane surface area). Simultaneous activation of membrane processes may be what is required to accelerate growth of the fastest-growing form of eukaryotic life to growth rates that are even faster, and may be of potential interest for single-cell protein production in industrial 'White' biotechnology processes.

Effect of late promoter activity on bacteriophage lambda fitness

For many bacteriophages (phages), the proteins responsible for host lysis and virion morphogenesis are expressed from the same polycistronic transcript. Such an expression pattern can potentially have a pleiotropic effect on the assembly rate and lysis time, thus affecting phage fitness. To study the effects of late promoter activity on phage life history traits and fitness, we constructed a series of isogenic phage lambda strains that differ only in their late promoter pR' sequences. The resulting late promoter activities ranged from 6 to 100% of the wild type's. The lysis times, burst sizes, and relative fitness were empirically determined for these strains. Our results showed that the lysis time is more sensitive than the assembly rate to variation in pR' activity. However, except for the strain with the lowest activity, the relative fitnesses of all the other strains are not significantly different from each other. Ad hoc models describing the effects of the late promoter activity on lysis time and assembly rate were constructed. The expected phage burst size and fitness curve were predicted from these models. Evolution of the late promoter activity was discussed in the context of phage life history trait evolution.

Construction of a synthetic YdbK-dependent pyruvate:H2 pathway in Escherichia coli BL21(DE3)

A synthetic pyruvate:H(2) pathway was constructed in Escherichia coli BL21(DE3) by co-expression of six proteins: E. coli YdbK, Clostridium pasteurianum [4Fe-4S]-ferredoxin, and Clostridium acetobutylicum HydF, HydE, HydG, and HydA. The effect of cofactor addition and host strain on H(2) yield and fermentation product accumulation was studied, together with in vitro reconstitution of the entire pathway. The deletion of iscR and/or the addition of thiamine pyrophosphate to the medium enhanced the total and specific activity of recombinant YdbK and increased the yield of H(2) per glucose. It was concluded that the introduced pathway outcompeted other pyruvate-consuming reactions, and that the ability to compete for pyruvate at least in part was determined by total YdbK activity. The results demonstrate the successful construction of a high-yielding H(2) pathway in a microorganism that effectively does not synthesize any H(2). The additional co-expression of Bacillus subtilis AmyE enabled starch-dependent H(2) synthesis in minimal media.

Lower respiratory capacity in extraocular muscle mitochondria: evidence for intrinsic differences in mitochondrial composition and function

PURPOSE

The constant activity of the extraocular muscles is supported by abundant mitochondria. These organelles may enhance energy production by increasing the content of respiratory complexes. The authors tested the hypothesis that extraocular muscle mitochondria respire faster than do mitochondria from limb muscles because of the higher content of respiratory complexes.

METHODS

Inner mitochondrial membrane density was determined by stereological analysis of triceps surae (a limb muscle) and extraocular muscles of adult male Sprague-Dawley rats. The authors measured respiration rates of isolated mitochondria using a Clark-type electrode. The activity of respiratory complexes I, II, and IV was determined by spectrophotometry. The content of respiratory complexes was estimated by Western blot.

RESULTS

States 3, 4, and 5 respiration rates in extraocular muscle mitochondria were 40% to 60% lower than in limb muscle mitochondria. Extraocular muscle inner mitochondrial membrane density was similar to that of other skeletal muscles. Activity of complexes I and IV was lower in extraocular muscle mitochondria (approximately 50% the activity in triceps), but their content was approximately 15% to 30% higher. There was no difference in complex II content or activity or complex III content. Finally, complex V was less abundant in extraocular muscle mitochondria.

CONCLUSIONS

The results demonstrate that extraocular muscle mitochondria respire at slower rates than mitochondria from limb muscles, despite similar mitochondrial ultrastructure. Instead, differences were found in the activity (I, IV) and content (I, IV, V) of electron transport chain complexes. The discrepancy between activity and content of some complexes is suggestive of alternative subunit isoform expression in the extraocular muscles compared with limb muscles.

Sensitivity analysis: from model parameters to system behaviour

Sensitivity analysis addresses the manner in which model behaviour depends on model parametrization. Global sensitivity analysis makes use of statistical tools to address system behaviour over a wide range of operating conditions, whereas local sensitivity analysis focuses attention on a specific set of nominal parameter values. This narrow focus allows a complete analytical treatment and straightforward interpretation in the local case. Sensitivity analysis is a valuable tool for model construction and interpretation, and can be applied in medicine and biotechnology to predict the effect of interventions.

Linear analysis near a steady-state of biochemical networks: control analysis, correlation metrics and circuit theory

Background

Several approaches, including metabolic control analysis (MCA), flux balance analysis (FBA), correlation metric construction (CMC), and biochemical circuit theory (BCT), have been developed for the quantitative analysis of complex biochemical networks. Here, we present a comprehensive theory of linear analysis for nonequilibrium steady-state (NESS) biochemical reaction networks that unites these disparate approaches in a common mathematical framework and thermodynamic basis.

Results

In this theory a number of relationships between key matrices are introduced: the matrix A obtained in the standard, linear-dynamic-stability analysis of the steady-state can be decomposed as A = SR^T where R and S are directly related to the elasticity-coefficient matrix for the fluxes and chemical potentials in MCA, respectively; the control-coefficients for the fluxes and chemical potentials can be written in terms of R^TBS and S^TBS respectively where matrix B is the inverse of A; the matrix S is precisely the stoichiometric matrix in FBA; and the matrix e^At plays a central role in CMC.

Conclusion

One key finding that emerges from this analysis is that the well-known summation theorems in MCA take different forms depending on whether metabolic steady-state is maintained by flux injection or concentration clamping. We demonstrate that if rate-limiting steps exist in a biochemical pathway, they are the steps with smallest biochemical conductances and largest flux control-coefficients. We hypothesize that biochemical networks for cellular signaling have a different strategy for minimizing energy waste and being efficient than do biochemical networks for biosynthesis. We also discuss the intimate relationship between MCA and biochemical systems analysis (BSA).

Human metabolic network reconstruction and its impact on drug discovery and development

This paper describes the process for the reconstruction of a high quality human metabolic network from the genome information, the existing problems in the reconstruction and why a time-consuming literature based consolidation process is needed. The reconstructed metabolic network provides a unified platform to integrate all the biological and medical information on genes, proteins, metabolites, disease, drugs and drug targets for a system level study of the relationship between metabolism and disease. System analysis of metabolic networks will help us, not only in identifying new drug targets but also in developing a system-oriented drug design strategy.