The Experts below are selected from a list of 64329 Experts worldwide ranked by ideXlab platform
Hans V Westerhoff - One of the best experts on this subject based on the ideXlab platform.
-
im perfect robustness and adaptation of Metabolic networks subject to Metabolic and gene expression regulation marrying Control engineering with Metabolic Control Analysis
BMC Systems Biology, 2013Co-Authors: Vincent Fromion, Hans V WesterhoffAbstract:Metabolic Control Analysis (MCA) and supply–demand theory have led to appreciable understanding of the systems properties of Metabolic networks that are subject exclusively to Metabolic regulation. Supply–demand theory has not yet considered gene-expression regulation explicitly whilst a variant of MCA, i.e. Hierarchical Control Analysis (HCA), has done so. Existing analyses based on Control engineering approaches have not been very explicit about whether Metabolic or gene-expression regulation would be involved, but designed different ways in which regulation could be organized, with the potential of causing adaptation to be perfect. This study integrates Control engineering and classical MCA augmented with supply–demand theory and HCA. Because gene-expression regulation involves time integration, it is identified as a natural instantiation of the ‘integral Control’ (or near integral Control) known in Control engineering. This study then focuses on robustness against and adaptation to perturbations of process activities in the network, which could result from environmental perturbations, mutations or slow noise. It is shown however that this type of ‘integral Control’ should rarely be expected to lead to the ‘perfect adaptation’: although the gene-expression regulation increases the robustness of important metabolite concentrations, it rarely makes them infinitely robust. For perfect adaptation to occur, the protein degradation reactions should be zero order in the concentration of the protein, which may be rare biologically for cells growing steadily. A proposed new framework integrating the methodologies of Control engineering and Metabolic and hierarchical Control Analysis, improves the understanding of biological systems that are regulated both Metabolically and by gene expression. In particular, the new approach enables one to address the issue whether the intracellular biochemical networks that have been and are being identified by genomics and systems biology, correspond to the ‘perfect’ regulatory structures designed by Control engineering vis-a-vis optimal functions such as robustness. To the extent that they are not, the analyses suggest how they may become so and this in turn should facilitate synthetic biology and Metabolic engineering.
-
Metabolic Control Analysis indicates a change of strategy in the treatment of cancer
Mitochondrion, 2010Co-Authors: Rafael Morenosanchez, Emma Saavedra, Sara Rodriguezenriquez, Hans V Westerhoff, Juan Carlos Gallardoperez, Hector QuezadaAbstract:Much of the search for the "magic cancer bullet" or "block buster" has followed the expectation of a single gene or protein as "the rate-limiting step" for tumor persistence. Examples continue to abound: EGFR, VEGFR, Akt/PI3K, HIF-1α, PHD, PDK, or FAS continue to be targeted individually. However, many such attempts to block a Metabolic or signal transduction pathway by targeting, specifically, a single rate-limiting molecule have proven to be unsuccessful. Metabolic Control Analysis (MCA) of cancer cells has generated a generic explanation for this phenomenon: several steps share the Control of energy metabolism (for glycolysis: glucose transporter, hexokinase, glycogen synthesis and ATP demand; for oxidative phosphorylation: respiratory complex I and ATP demand), i.e., there is no single "rate-limiting step". Targeting a type of step that does not exist is unlikely to be a successful paradigm for continued research into drug targeting of cancer. MCA establishes how to determine, quantitatively, the degrees of Control that the various enzymes in the intracellular network exert on vital flux (or function) and on the concentration of important metabolites, substituting for the intuitive, qualitative and most often erroneous concept of single rate-limiting step. Moreover, MCA helps to understand (i) the underlying mechanisms by which a given enzyme exerts high or low Control, (ii) why the Control of the pathway is shared by several pathway enzymes and transporters and (iii) what are the better sets of drug targets. Indeed, by applying MCA it should now be possible to identify the group of proteins (and genes) that should be modified to achieve a successful modulation of the intracellular networks of biotechnological or clinical relevance. The challenge is to move away from the design of drugs that specifically inhibit a single Controlling step, towards unspecific drugs or towards drug mixtures, which may have multiple target sites in the most exacerbated, unique and Controlling pathways in cancer cells. Successful nonspecific drugs should still be specific for the networks of cancer cells over those of normal cells and to establish such cell-type specificity within molecular non-specificity will continue to require sophisticated analyses. Clinical practice has anticipated the latter strategy of mixtures of drugs: combinations of anti-neoplastic drugs are already administered with encouraging results. Therefore, the most promising strategy for cancer treatment seems to be that of a multi-targeted, MCA-advised, therapy.
-
Metabolic Control Analysis to identify optimal drug targets
Progress in drug research, 2007Co-Authors: Jorrit J Hornberg, Hans V Westerhoff, Barbara M Bakker, Frank J BruggemanAbstract:This chapter describes the basic principles of Metabolic Control Analysis (MCA) which is a quantitative methodology to evaluate the importance and relative contribution of individual Metabolic steps in the overall functioning of a particular system. The Control on the flux through a Metabolic pathway or subsystem can be quantified by the Control coefficients of the individual enzymes or components which reflects the extent to which the component is rate-limiting. The perturbation of an individual step is measured by its elasticity coefficient. The effect of perturbation of a single step on the entire pathway or subsystemis, in turn, measured by the response coefficient. Differential Control Analysis can be used to compare flux through a single Metabolic pathway in a pathogen with the same pathway in its host to identify uniquely vulnerable steps with the greatest potential for specifically inhibiting flux through the pathogen Metabolic pathway. The utility of this methodology is illustrated with the glycolysis in Trypanosomes and with oncogenic signaling.
-
Metabolic Control of mitochondrial properties by adenine nucleotide translocator determines palmitoyl coa effects
FEBS Journal, 2006Co-Authors: Hans V Westerhoff, Jolita Ciapaite, Gerco Van Eikenhorst, Stephan J L Bakker, Michaela Diamant, Robert J Heine, Klaas KrabAbstract:Inhibition of the mitochondrial adenine nucleotide translocator (ANT) by long-chain acyl-CoA esters has been proposed to contribute to cellular dysfunction in obesity and type 2 diabetes by increasing formation of reactive oxygen species and adenosine via effects on the coenzyme Q redox state, mitochondrial membrane potential (Delta psi) and cytosolic ATP concentrations. We here show that 5 mu M palmitoyl-CoA increases the ratio of reduced to oxidized coenzyme Q (QH(2)/Q) by 42 +/- 9%, Delta psi by 13 +/- 1 mV (9%), and the intramitochondrial ATP/ADP ratio by 352 +/- 34%, and decreases the extramitochondrial ATP/ADP ratio by 63 +/- 4% in actively phosphorylating mitochondria. The latter reduction is expected to translate into a 24% higher extramitochondrial AMP concentration. Furthermore, palmitoyl-CoA induced concentration-dependent H2O2 formation, which can only partly be explained by its effect on Delta psi. Although all measured fluxes and intermediate concentrations were affected by palmitoyl-CoA, modular kinetic Analysis revealed that this resulted mainly from inhibition of the ANT. Through Metabolic Control Analysis, we then determined to what extent the ANT Controls the investigated mitochondrial properties. Under steady-state conditions, the ANT moderately Controlled oxygen uptake (Control coefficient C = 0.13) and phosphorylation (C = 0.14) flux. It Controlled intramitochondrial (C = -0.70) and extramitochondrial ATP/ADP ratios (C = 0.23) more strongly, whereas the Control exerted over the QH(2)/Q ratio (C = -0.04) and Delta psi (C = -0.01) was small. Quantitative assessment of the effects of palmitoyl-CoA showed that the mitochondrial properties that were most strongly Controlled by the ANT were affected the most. Our observations suggest that long-chain acyl-CoA esters may contribute to cellular dysfunction in obesity and type 2 diabetes through effects on cellular energy metabolism and production of reactive oxygen species.
-
Metabolic Control Analysis of the atpase network in contracting muscle regulation of contractile function and atp free energy potential
2004Co-Authors: J A L Jeneson, Hans V Westerhoff, Martin J KushmerickAbstract:Skeletal muscle converts the thermodynamic force of the non-equilibrium ATP/ADP concentration ratio in the cytosol into mechanical force during contrac-tion1 [1]. As such, skeletal muscle function can be described using engineering concepts as a chemo-mechano transducer (Fig. 1). The molecular machinery in-volved in this conversion consists, amongst others, of filaments of actin and the motor protein myosin ATPase, and the calcium (Ca2+)-activated switch protein troponin [1]. The non-equilibrium cytosolic ATP/ADP concentration potential is thermodynamically buffered by the cellular pool of mitochondria via oxidative ADP phosphorylation. Kinetically, this cytosolic potential is buffered on a fast (i.e. (sub)second) time scale by creatine kinase (CK) and glycolysis, and on a slow (i.e. minutes) timescale by oxidative phosphorylation [2]. Muscle contraction and the associated conversion of thermodynamic ATP energy force is under voluntary, neural Control [1]. It is initiated at the cellular level by action potential-gated re-lease of Ca2+ions from the sarcoplasmic reticulum (SR) stores into the myoplasm2.
John L Harwood - One of the best experts on this subject based on the ideXlab platform.
-
Increase in lysophosphatidate acyltransferase activity in oilseed rape (Brassica napus) increases seed triacylglycerol content despite its low intrinsic flux Control coefficient
The New phytologist, 2019Co-Authors: Helen Woodfield, Irina A. Guschina, David A Fell, Stepan Fenyk, Emma J. Wallington, Ruth Bates, Alex Brown, Elizabeth-france Marillia, David C. Taylor, John L HarwoodAbstract:Lysophosphatidate acyltransferase (LPAAT ) catalyses the second step of the Kennedy pathway for triacylglycerol (TAG ) synthesis. In this study we expressed Trapaeolum majus LPAAT in Brassica napus (B. napus ) cv 12075 to evaluate the effects on lipid synthesis and estimate the flux Control coefficient for LPAAT . We estimated the flux Control coefficient of LPAAT in a whole plant context by deriving a relationship between it and overall lipid accumulation, given that this process is a exponential. Increasing LPAAT activity resulted in greater TAG accumulation in seeds of between 25% and 29%; altered fatty acid distributions in seed lipids (particularly those of the Kennedy pathway); and a redistribution of label from 14C‐glycerol between phosphoglycerides. Greater LPAAT activity in seeds led to an increase in TAG content despite its low intrinsic flux Control coefficient on account of the exponential nature of lipid accumulation that amplifies the effect of the small flux increment achieved by increasing its activity. We have also developed a novel application of Metabolic Control Analysis likely to have broad application as it determines the in planta flux Control that a single component has upon accumulation of storage products.
-
studies on the regulation of lipid biosynthesis in plants application of Control Analysis to soybean
Biochimica et Biophysica Acta, 2014Co-Authors: Irina A. Guschina, Patti A. Quant, John D Everard, Anthony J Kinney, John L HarwoodAbstract:Although there is much knowledge of the enzymology (and genes coding the proteins) of lipid biosynthesis in higher plants, relatively little attention has been paid to regulation. We have demonstrated the important role for cholinephosphate cytidylyltransferase in the biosynthesis of the major extra-plastidic membrane lipid, phosphatidylcholine. We followed this work by applying Control Analysis to light-induced fatty acid synthesis. This was the first such application to lipid synthesis in any organism. The data showed that acetyl-CoA carboxylase was very important, exerting about half of the total Control. We then applied Metabolic Control Analysis to lipid accumulation in important oil crops - oilpalm, olive, and rapeseed. Recent data with soybean show that the block of fatty acid biosynthesis reactions exerts somewhat more Control (63%) than lipid assembly although both are clearly very important. These results suggest that gene stacks, targeting both parts of the overall lipid synthesis pathway will be needed to increase significantly oil yields in soybean. This article is part of a Special Issue entitled: Membrane Structure and Function: Relevance in the Cell's Physiology, Pathology and Therapy.
-
informed Metabolic engineering of oil crops using Control Analysis
Biocatalysis and agricultural biotechnology, 2014Co-Authors: Umi S Ramli, Mingguo Tang, Irina A. Guschina, Tony Fawcett, Patti A. Quant, John L HarwoodAbstract:Oil crops are a very important agricultural commodity. Demand for such oils is rising steadily (at more than 5% per year over the last half century). Although the majority of plant oils are used for food or animal feed, there is increasing interest in their use as renewable chemicals for industry. Because of the demonstrated demand for oils and finite agricultural land, attention is focussing on improving productivity. Genetic manipulation of crop plants needs a knowledge of the biosynthetic pathways concerned and how they are regulated. Although there are different ways to acquire much information, Metabolic flux and Metabolic Control analyses are ways to provide quantitative assessments. In this review we describe our experiments using Metabolic Control Analysis on important crops – oil palm, oilseed rape, olive and soybean. Such research provides information for future informed genetic manipulations and we give a successful example of this in oilseed rape (Brassica napus L.).
-
regulation and enhancement of lipid accumulation in oil crops the use of Metabolic Control Analysis for informed genetic manipulation
European Journal of Lipid Science and Technology, 2013Co-Authors: John L Harwood, Mingguo Tang, Tony Fawcett, Patti A. Quant, Umi S Ramli, Randall J Weselake, Irina A. GuschinaAbstract:Plant oils are a very valuable agricultural commodity. They are currently mainly used (>80%) for food and animal feed but, increasingly, they have utility as renewable sources of industrial feedstocks or biofuel. Because of finite agricultural land, the best way to increase availability (in order to match demand) is by improving productivity. To do this requires a knowledge of metabolism and its regulation. Various methods have been used to provide information but only systems biology can yield quantitative data about complete Metabolic pathways. We have used Metabolic Control Analysis to provide information about major oil crops such as oilseed rape, oil palm, olive, and soybean. Such knowledge has then been used to inform genetic manipulation for crop improvement.
-
Metabolic Control Analysis of developing oilseed rape (brassica napus cv Westar) embryos shows that lipid assembly exerts significant Control over oil accumulation
New Phytologist, 2012Co-Authors: Mingguo Tang, Paul O'hara, Irina A. Guschina, Tony Fawcett, Patti A. Quant, Antoni R Slabas, John L HarwoodAbstract:Summary\r\n•\r\nMetabolic Control Analysis allows the study of Metabolic regulation. We applied both single- and double-manipulation top-down Control Analysis to examine the Control of lipid accumulation in developing oilseed rape (Brassica napus) embryos.\r\n•\r\nThe biosynthetic pathway was conceptually divided into two blocks of reactions (fatty acid biosynthesis (Block A), lipid assembly (Block B)) connected by a single system intermediate, the acyl-coenzyme A (acyl-CoA) pool. Single manipulation used exogenous oleate. Triclosan was used to inhibit specifically Block A, whereas diazepam selectively manipulated flux through Block B.\r\n•\r\nExogenous oleate inhibited the radiolabelling of fatty acids from [1-14C]acetate, but stimulated that from [U-14C]glycerol into acyl lipids. The calculation of group flux Control coefficients showed that c. 70% of the Metabolic Control was in the lipid assembly block of reactions. Monte Carlo simulations gave an estimation of the error of the resulting group flux Control coefficients as 0.27 ± 0.06 for Block A and 0.73 ± 0.06 for Block B.\r\n•\r\nThe two methods of Control Analysis gave very similar results and showed that Block B reactions were more important under our conditions. This contrasts notably with data from oil palm or olive fruit cultures and is important for efforts to increase oilseed rape lipid yields.
Patti A. Quant - One of the best experts on this subject based on the ideXlab platform.
-
studies on the regulation of lipid biosynthesis in plants application of Control Analysis to soybean
Biochimica et Biophysica Acta, 2014Co-Authors: Irina A. Guschina, Patti A. Quant, John D Everard, Anthony J Kinney, John L HarwoodAbstract:Although there is much knowledge of the enzymology (and genes coding the proteins) of lipid biosynthesis in higher plants, relatively little attention has been paid to regulation. We have demonstrated the important role for cholinephosphate cytidylyltransferase in the biosynthesis of the major extra-plastidic membrane lipid, phosphatidylcholine. We followed this work by applying Control Analysis to light-induced fatty acid synthesis. This was the first such application to lipid synthesis in any organism. The data showed that acetyl-CoA carboxylase was very important, exerting about half of the total Control. We then applied Metabolic Control Analysis to lipid accumulation in important oil crops - oilpalm, olive, and rapeseed. Recent data with soybean show that the block of fatty acid biosynthesis reactions exerts somewhat more Control (63%) than lipid assembly although both are clearly very important. These results suggest that gene stacks, targeting both parts of the overall lipid synthesis pathway will be needed to increase significantly oil yields in soybean. This article is part of a Special Issue entitled: Membrane Structure and Function: Relevance in the Cell's Physiology, Pathology and Therapy.
-
informed Metabolic engineering of oil crops using Control Analysis
Biocatalysis and agricultural biotechnology, 2014Co-Authors: Umi S Ramli, Mingguo Tang, Irina A. Guschina, Tony Fawcett, Patti A. Quant, John L HarwoodAbstract:Oil crops are a very important agricultural commodity. Demand for such oils is rising steadily (at more than 5% per year over the last half century). Although the majority of plant oils are used for food or animal feed, there is increasing interest in their use as renewable chemicals for industry. Because of the demonstrated demand for oils and finite agricultural land, attention is focussing on improving productivity. Genetic manipulation of crop plants needs a knowledge of the biosynthetic pathways concerned and how they are regulated. Although there are different ways to acquire much information, Metabolic flux and Metabolic Control analyses are ways to provide quantitative assessments. In this review we describe our experiments using Metabolic Control Analysis on important crops – oil palm, oilseed rape, olive and soybean. Such research provides information for future informed genetic manipulations and we give a successful example of this in oilseed rape (Brassica napus L.).
-
regulation and enhancement of lipid accumulation in oil crops the use of Metabolic Control Analysis for informed genetic manipulation
European Journal of Lipid Science and Technology, 2013Co-Authors: John L Harwood, Mingguo Tang, Tony Fawcett, Patti A. Quant, Umi S Ramli, Randall J Weselake, Irina A. GuschinaAbstract:Plant oils are a very valuable agricultural commodity. They are currently mainly used (>80%) for food and animal feed but, increasingly, they have utility as renewable sources of industrial feedstocks or biofuel. Because of finite agricultural land, the best way to increase availability (in order to match demand) is by improving productivity. To do this requires a knowledge of metabolism and its regulation. Various methods have been used to provide information but only systems biology can yield quantitative data about complete Metabolic pathways. We have used Metabolic Control Analysis to provide information about major oil crops such as oilseed rape, oil palm, olive, and soybean. Such knowledge has then been used to inform genetic manipulation for crop improvement.
-
Metabolic Control Analysis of developing oilseed rape (brassica napus cv Westar) embryos shows that lipid assembly exerts significant Control over oil accumulation
New Phytologist, 2012Co-Authors: Mingguo Tang, Paul O'hara, Irina A. Guschina, Tony Fawcett, Patti A. Quant, Antoni R Slabas, John L HarwoodAbstract:Summary\r\n•\r\nMetabolic Control Analysis allows the study of Metabolic regulation. We applied both single- and double-manipulation top-down Control Analysis to examine the Control of lipid accumulation in developing oilseed rape (Brassica napus) embryos.\r\n•\r\nThe biosynthetic pathway was conceptually divided into two blocks of reactions (fatty acid biosynthesis (Block A), lipid assembly (Block B)) connected by a single system intermediate, the acyl-coenzyme A (acyl-CoA) pool. Single manipulation used exogenous oleate. Triclosan was used to inhibit specifically Block A, whereas diazepam selectively manipulated flux through Block B.\r\n•\r\nExogenous oleate inhibited the radiolabelling of fatty acids from [1-14C]acetate, but stimulated that from [U-14C]glycerol into acyl lipids. The calculation of group flux Control coefficients showed that c. 70% of the Metabolic Control was in the lipid assembly block of reactions. Monte Carlo simulations gave an estimation of the error of the resulting group flux Control coefficients as 0.27 ± 0.06 for Block A and 0.73 ± 0.06 for Block B.\r\n•\r\nThe two methods of Control Analysis gave very similar results and showed that Block B reactions were more important under our conditions. This contrasts notably with data from oil palm or olive fruit cultures and is important for efforts to increase oilseed rape lipid yields.
-
Use of Metabolic Control Analysis to give quantitative information on Control of lipid biosynthesis in the important oil crop, Elaeis guineensis (oilpalm)
The New phytologist, 2009Co-Authors: Umi S Ramli, Patti A. Quant, Joaquín J. Salas, John L HarwoodAbstract:* Oil crops are a very important commodity. Although many genes and enzymes involved in lipid accumulation have been identified, much less is known of regulation of the overall process. To address the latter we have applied Metabolic Control Analysis to lipid synthesis in the important crop, oilpalm (Elaeis guineensis). * Top-down Metabolic Control Analysis (TDCA) was applied to callus cultures capable of accumulating appreciable triacylglycerol. The biosynthetic pathway was divided into two blocks, connected by the intermediate acyl-CoAs. Block A comprised enzymes for fatty acid synthesis and Block B comprised enzymes of lipid assembly. * Double manipulation TDCA used diflufenican and bromooctanoate to inhibit Block A and Block B, respectively, giving Block flux Control coefficients of 0.61 and 0.39. Monte Carlo simulations provided extra information from previously-reported single manipulation TDCA data, giving Block flux Control coefficients of 0.65 and 0.35 for A and B. * These experiments are the first time that double manipulation TDCA has been applied to lipid biosynthesis in any organism. The data show that approaching two-thirds of the total Control of carbon flux to lipids in oilpalm cultures lies with the fatty acid synthesis block of reactions. This quantitative information will assist future, informed, genetic manipulation of oilpalm.
Vassily Hatzimanikatis - One of the best experts on this subject based on the ideXlab platform.
-
constraint based Metabolic Control Analysis for rational strain engineering
Metabolic Engineering, 2021Co-Authors: Sofia Tsouka, Meric Ataman, Tuure Hameri, Ljubisa Miskovic, Vassily HatzimanikatisAbstract:The advancements in genome editing techniques over the past years have rekindled interest in rational Metabolic engineering strategies. While Metabolic Control Analysis (MCA) is a well-established method for quantifying the effects of Metabolic engineering interventions on flows in Metabolic networks and metabolite concentrations, it does not consider the physiological limitations of the cellular environment and Metabolic engineering design constraints. We report here a constraint-based framework, Network Response Analysis (NRA), for rational genetic strain design. NRA is cast as a Mixed-Integer Linear Programming problem that integrates MCA, Thermodynamically-based Flux Analysis (TFA), biologically relevant constraints, as well as genome editing restrictions into a comprehensive platform for identifying Metabolic engineering targets. We show that the NRA formulation and its core constraints are equivalent to the ones of Flux Balance Analysis (FBA) and TFA, which allows it to be used for a wide range of optimization criteria and with various physiological constraints. We also show how the parametrization and introduction of biological constraints enhance the NRA formulation compared to the classical MCA approach, and we demonstrate its features and its ability to generate multiple alternative optimal strategies given several user-defined boundaries and objectives. In summary, NRA is a sophisticated alternative to classical MCA for rational Metabolic engineering that accommodates the incorporation of physiological data at Metabolic flux, metabolite concentration, and enzyme expression levels.
-
constraint based Metabolic Control Analysis for rational strain engineering
bioRxiv, 2020Co-Authors: Sofia Tsouka, Meric Ataman, Tuure Hameri, Ljubisa Miskovic, Vassily HatzimanikatisAbstract:The advancements in genome editing techniques over the past years have rekindled interest in rational Metabolic engineering strategies. While Metabolic Control Analysis (MCA) is a well-established method for quantifying the effects of Metabolic engineering interventions on flows in Metabolic networks and Metabolic concentrations, it fails to account for the physiological limitations of the cellular environment and Metabolic engineering design constraints. We report here a constraint-based framework based on MCA, Network Response Analysis (NRA), for the rational genetic strain design that incorporates biologically relevant constraints, as well as genome editing restrictions. The NRA core constraints being similar to the ones of Flux Balance Analysis, allow it to be used for a wide range of optimization criteria and with various physiological constraints. We show how the parametrization and introduction of biological constraints enhance the NRA formulation compared to the classical MCA approach, and we demonstrate its features and its ability to generate multiple alternative optimal strategies given several user-defined boundaries and objectives. In summary, NRA is a sophisticated alternative to classical MCA for rational Metabolic engineering that accommodates the incorporation of physiological data at Metabolic flux, metabolite concentration, and enzyme expression levels.
-
statistical inference in ensemble modeling of cellular metabolism
PLOS Computational Biology, 2019Co-Authors: Tuure Hameri, Marcolivier Boldi, Vassily HatzimanikatisAbstract:Kinetic models of metabolism can be constructed to predict cellular regulation and devise Metabolic engineering strategies, and various promising computational workflows have been developed in recent years for this. Due to the uncertainty in the kinetic parameter values required to build kinetic models, these workflows rely on ensemble modeling (EM) principles for sampling and building populations of models describing observed physiologies. Sensitivity coefficients from Metabolic Control Analysis (MCA) of kinetic models can provide important insight about cellular Control around a given physiological steady state. However, despite considering populations of kinetic models and their model outputs, current approaches do not provide adequate tools for statistical inference. To derive conclusions from model outputs, such as MCA sensitivity coefficients, it is necessary to rank/compare populations of variables with each other. Currently existing workflows consider confidence intervals (CIs) that are derived independently for each comparable variable. Hence, it is important to derive simultaneous CIs for the variables that we wish to rank/compare. Herein, we used an existing large-scale kinetic model of Escherichia Coli metabolism to present how univariate CIs can lead to incorrect conclusions, and we present a new workflow that applies three different multivariate statistical approaches. We use the Bonferroni and the exact normal methods to build symmetric CIs using the normality assumptions. We then suggest how bootstrapping can compute asymmetric CIs whilst relaxing this normality assumption. We conclude that the Bonferroni and the exact normal methods can provide simple and efficient ways for constructing reliable CIs, with the exact normal method favored over the Bonferroni when the compared variables present dependencies. Bootstrapping, despite its significantly higher computational cost, is recommended when comparing non-normal distributions of variables. Additionally, we show how the Bonferroni method can readily be used to estimate required sample numbers to attain a certain CI size.
-
a method for Analysis and design of metabolism using metabolomics data and kinetic models application on lipidomics using a novel kinetic model of sphingolipid metabolism
Metabolic Engineering, 2016Co-Authors: Georgios Savoglidis, Aline X S Santos, Isabelle Riezman, P Angelino, Howard Riezman, Vassily HatzimanikatisAbstract:We present a model-based method, designated Inverse Metabolic Control Analysis (IMCA), which can be used in conjunction with classical Metabolic Control Analysis for the Analysis and design of cellular metabolism. We demonstrate the capabilities of the method by first developing a comprehensively curated kinetic model of sphingolipid biosynthesis in the yeast Saccharomyces cerevisiae. Next we apply IMCA using the model and integrating lipidomics data. The combinatorial complexity of the synthesis of sphingolipid molecules, along with the operational complexity of the participating enzymes of the pathway, presents an excellent case study for testing the capabilities of the IMCA. The exceptional agreement of the predictions of the method with genome-wide data highlights the importance and value of a comprehensive and consistent engineering approach for the development of such methods and models. Based on the Analysis, we identified the class of enzymes regulating the distribution of sphingolipids among species and hydroxylation states, with the D-phospholipase SPO14 being one of the most prominent. The method and the applications presented here can be used for a broader, model-based inverse Metabolic engineering approach.
-
Metabolic Control Analysis under uncertainty framework development and case studies
Biophysical Journal, 2004Co-Authors: Liqing Wang, Inanc Birol, Vassily HatzimanikatisAbstract:Information about the enzyme kinetics in a Metabolic network will enable understanding of the function of the network and quantitative prediction of the network responses to genetic and environmental perturbations. Despite recent advances in experimental techniques, such information is limited and existing experimental data show extensive variation and they are based on in vitro experiments. In this article, we present a computational framework based on the well-established (log)linear formalism of Metabolic Control Analysis. The framework employs a Monte Carlo sampling procedure to simulate the uncertainty in the kinetic data and applies statistical tools for the identification of the rate-limiting steps in Metabolic networks. We applied the proposed framework to a branched biosynthetic pathway and the yeast glycolysis pathway. Analysis of the results allowed us to interpret and predict the responses of Metabolic networks to genetic and environmental changes, and to gain insights on how uncertainty in the kinetic mechanisms and kinetic parameters propagate into the uncertainty in predicting network responses. Some of the practical applications of the proposed approach include the identification of drug targets for Metabolic diseases and the guidance for design strategies in Metabolic engineering for the purposeful manipulation of the metabolism of industrial organisms.
Irina A. Guschina - One of the best experts on this subject based on the ideXlab platform.
-
Increase in lysophosphatidate acyltransferase activity in oilseed rape (Brassica napus) increases seed triacylglycerol content despite its low intrinsic flux Control coefficient
The New phytologist, 2019Co-Authors: Helen Woodfield, Irina A. Guschina, David A Fell, Stepan Fenyk, Emma J. Wallington, Ruth Bates, Alex Brown, Elizabeth-france Marillia, David C. Taylor, John L HarwoodAbstract:Lysophosphatidate acyltransferase (LPAAT ) catalyses the second step of the Kennedy pathway for triacylglycerol (TAG ) synthesis. In this study we expressed Trapaeolum majus LPAAT in Brassica napus (B. napus ) cv 12075 to evaluate the effects on lipid synthesis and estimate the flux Control coefficient for LPAAT . We estimated the flux Control coefficient of LPAAT in a whole plant context by deriving a relationship between it and overall lipid accumulation, given that this process is a exponential. Increasing LPAAT activity resulted in greater TAG accumulation in seeds of between 25% and 29%; altered fatty acid distributions in seed lipids (particularly those of the Kennedy pathway); and a redistribution of label from 14C‐glycerol between phosphoglycerides. Greater LPAAT activity in seeds led to an increase in TAG content despite its low intrinsic flux Control coefficient on account of the exponential nature of lipid accumulation that amplifies the effect of the small flux increment achieved by increasing its activity. We have also developed a novel application of Metabolic Control Analysis likely to have broad application as it determines the in planta flux Control that a single component has upon accumulation of storage products.
-
studies on the regulation of lipid biosynthesis in plants application of Control Analysis to soybean
Biochimica et Biophysica Acta, 2014Co-Authors: Irina A. Guschina, Patti A. Quant, John D Everard, Anthony J Kinney, John L HarwoodAbstract:Although there is much knowledge of the enzymology (and genes coding the proteins) of lipid biosynthesis in higher plants, relatively little attention has been paid to regulation. We have demonstrated the important role for cholinephosphate cytidylyltransferase in the biosynthesis of the major extra-plastidic membrane lipid, phosphatidylcholine. We followed this work by applying Control Analysis to light-induced fatty acid synthesis. This was the first such application to lipid synthesis in any organism. The data showed that acetyl-CoA carboxylase was very important, exerting about half of the total Control. We then applied Metabolic Control Analysis to lipid accumulation in important oil crops - oilpalm, olive, and rapeseed. Recent data with soybean show that the block of fatty acid biosynthesis reactions exerts somewhat more Control (63%) than lipid assembly although both are clearly very important. These results suggest that gene stacks, targeting both parts of the overall lipid synthesis pathway will be needed to increase significantly oil yields in soybean. This article is part of a Special Issue entitled: Membrane Structure and Function: Relevance in the Cell's Physiology, Pathology and Therapy.
-
informed Metabolic engineering of oil crops using Control Analysis
Biocatalysis and agricultural biotechnology, 2014Co-Authors: Umi S Ramli, Mingguo Tang, Irina A. Guschina, Tony Fawcett, Patti A. Quant, John L HarwoodAbstract:Oil crops are a very important agricultural commodity. Demand for such oils is rising steadily (at more than 5% per year over the last half century). Although the majority of plant oils are used for food or animal feed, there is increasing interest in their use as renewable chemicals for industry. Because of the demonstrated demand for oils and finite agricultural land, attention is focussing on improving productivity. Genetic manipulation of crop plants needs a knowledge of the biosynthetic pathways concerned and how they are regulated. Although there are different ways to acquire much information, Metabolic flux and Metabolic Control analyses are ways to provide quantitative assessments. In this review we describe our experiments using Metabolic Control Analysis on important crops – oil palm, oilseed rape, olive and soybean. Such research provides information for future informed genetic manipulations and we give a successful example of this in oilseed rape (Brassica napus L.).
-
regulation and enhancement of lipid accumulation in oil crops the use of Metabolic Control Analysis for informed genetic manipulation
European Journal of Lipid Science and Technology, 2013Co-Authors: John L Harwood, Mingguo Tang, Tony Fawcett, Patti A. Quant, Umi S Ramli, Randall J Weselake, Irina A. GuschinaAbstract:Plant oils are a very valuable agricultural commodity. They are currently mainly used (>80%) for food and animal feed but, increasingly, they have utility as renewable sources of industrial feedstocks or biofuel. Because of finite agricultural land, the best way to increase availability (in order to match demand) is by improving productivity. To do this requires a knowledge of metabolism and its regulation. Various methods have been used to provide information but only systems biology can yield quantitative data about complete Metabolic pathways. We have used Metabolic Control Analysis to provide information about major oil crops such as oilseed rape, oil palm, olive, and soybean. Such knowledge has then been used to inform genetic manipulation for crop improvement.
-
Metabolic Control Analysis of developing oilseed rape (brassica napus cv Westar) embryos shows that lipid assembly exerts significant Control over oil accumulation
New Phytologist, 2012Co-Authors: Mingguo Tang, Paul O'hara, Irina A. Guschina, Tony Fawcett, Patti A. Quant, Antoni R Slabas, John L HarwoodAbstract:Summary\r\n•\r\nMetabolic Control Analysis allows the study of Metabolic regulation. We applied both single- and double-manipulation top-down Control Analysis to examine the Control of lipid accumulation in developing oilseed rape (Brassica napus) embryos.\r\n•\r\nThe biosynthetic pathway was conceptually divided into two blocks of reactions (fatty acid biosynthesis (Block A), lipid assembly (Block B)) connected by a single system intermediate, the acyl-coenzyme A (acyl-CoA) pool. Single manipulation used exogenous oleate. Triclosan was used to inhibit specifically Block A, whereas diazepam selectively manipulated flux through Block B.\r\n•\r\nExogenous oleate inhibited the radiolabelling of fatty acids from [1-14C]acetate, but stimulated that from [U-14C]glycerol into acyl lipids. The calculation of group flux Control coefficients showed that c. 70% of the Metabolic Control was in the lipid assembly block of reactions. Monte Carlo simulations gave an estimation of the error of the resulting group flux Control coefficients as 0.27 ± 0.06 for Block A and 0.73 ± 0.06 for Block B.\r\n•\r\nThe two methods of Control Analysis gave very similar results and showed that Block B reactions were more important under our conditions. This contrasts notably with data from oil palm or olive fruit cultures and is important for efforts to increase oilseed rape lipid yields.