Netherlands Consortium for Systems Biology
Netherlands Consortium for Systems Biology
Bakker B.M.,University of Groningen |
Bakker B.M.,Netherlands Institute for Systems Biology |
Van Eunen K.,University of Groningen |
Jeneson J.A.L.,Netherlands Consortium for Systems Biology |
And 5 more authors.
Biochemical Society Transactions | Year: 2010
Human metabolic diseases are typically network diseases. This holds not only for multifactorial diseases, such as metabolic syndrome or Type 2 diabetes, but even when a single gene defect is the primary cause, where the adaptive response of the entire network determines the severity of disease. The latter may differ between individuals carrying the same mutation. Understanding the adaptive responses of human metabolism naturally requires a systems biology approach. Modelling of metabolic pathways in microorganisms and some mammalian tissues has yielded many insights, qualitative as well as quantitative, into their control and regulation. Yet, even for a well-known pathway such as glycolysis, precise predictions of metabolite dynamics from experimentally determined enzyme kinetics have been only moderately successful. In the present review, we compare kinetic models of glycolysis in three cell types (African trypanosomes, yeast and skeletal muscle), evaluate their predictive power and identify limitations in our understanding. Although each of these models has its own merits and shortcomings, they also share common features. For example, in each case independently measured enzyme kinetic parameters were used as input. Based on these 'lessons from glycolysis', we will discuss how to make best use of kinetic computer models to advance our understanding of human metabolic diseases. ©The Authors Journal compilation ©2010 Biochemical Society.
Roldan M.V.G.,Netherlands Consortium for Systems Biology |
Roldan M.V.G.,Plant Research International |
Roldan M.V.G.,French National Institute for Agricultural Research |
Engel B.,Wageningen University |
And 22 more authors.
Metabolomics | Year: 2014
Tomato seedlings (Solanum lycopersicum cv. MoneyMaker), grown under strictly controlled conditions, have been used to study alterations occurring in secondary metabolite biosynthetic pathways following developmental and environmental perturbations. Robustness and reproducibility of the system were confirmed using detailed statistical analyses of the metabolome. LCMS profiling was applied using whole germinated seeds as well as cotyledons, hypocotyls and roots from 3 to 9 days old seedlings to generate relative levels of 433 metabolites, of which 62 were annotated. Initial focus was given to the polyphenol pathway and several additional mass signals have been putatively annotated using high mass resolution fragmentation. Clear organ and developmental stage-specific differences were observed. Seeds accumulated saponin-like compounds; roots accumulated mainly alkaloids; cotyledons contained mainly glycosylated flavonols and; hypocotyls contained mainly anthocyanins. For each organ, the developmental changes in metabolite profiles were described by using linear mixed models. Across three independent experiments, 85 % of the metabolites showed similar developmental trends. This tomato seedling system has given us valuable additional insights into the complexity of seedling secondary metabolism. How metabolic profiles reflect an interplay between depletion of stored molecules and de novo synthesis and how the overall picture for this important crop plant contrasts to e.g. Arabidopsis are emphasised. © 2014 Springer Science+Business Media New York.
de Jong J.,Netherlands Cancer Institute |
Akhtar W.,Netherlands Consortium for Systems Biology |
Akhtar W.,Netherlands Cancer Institute |
Badhai J.,Netherlands Cancer Institute |
And 9 more authors.
PLoS Genetics | Year: 2014
The ability of retroviruses and transposons to insert their genetic material into host DNA makes them widely used tools in molecular biology, cancer research and gene therapy. However, these systems have biases that may strongly affect research outcomes. To address this issue, we generated very large datasets consisting of ~120000 to ~180000 unselected integrations in the mouse genome for the Sleeping Beauty (SB) and piggyBac (PB) transposons, and the Mouse Mammary Tumor Virus (MMTV). We analyzed ~80 (epi)genomic features to generate bias maps at both local and genome-wide scales. MMTV showed a remarkably uniform distribution of integrations across the genome. More distinct preferences were observed for the two transposons, with PB showing remarkable resemblance to bias profiles of the Murine Leukemia Virus. Furthermore, we present a model where target site selection is directed at multiple scales. At a large scale, target site selection is similar across systems, and defined by domain-oriented features, namely expression of proximal genes, proximity to CpG islands and to genic features, chromatin compaction and replication timing. Notable differences between the systems are mainly observed at smaller scales, and are directed by a diverse range of features. To study the effect of these biases on integration sites occupied under selective pressure, we turned to insertional mutagenesis (IM) screens. In IM screens, putative cancer genes are identified by finding frequently targeted genomic regions, or Common Integration Sites (CISs). Within three recently completed IM screens, we identified 7%-33% putative false positive CISs, which are likely not the result of the oncogenic selection process. Moreover, results indicate that PB, compared to SB, is more suited to tag oncogenes. © 2014 de Jong et al.
Ciapaite J.,TU Eindhoven |
Ciapaite J.,University of Groningen |
van den Berg S.A.,Netherlands Consortium for Systems Biology |
van den Berg S.A.,Leiden University |
And 7 more authors.
Journal of Nutritional Biochemistry | Year: 2015
High-fat diets (HFDs) have been shown to interfere with skeletal muscle energy metabolism and cause peripheral insulin resistance. However, understanding of HFD impact on skeletal muscle primary function, i.e., contractile performance, is limited. Male C57BL/6J mice were fed HFD containing lard (HFL) or palm oil (HFP), or low-fat diet (LFD) for 5. weeks. Fast-twitch (FT) extensor digitorum longus (EDL) and slow-twitch (ST) soleus muscles were characterized with respect to contractile function and selected biochemical features. In FT EDL muscle, a 30%-50% increase in fatty acid (FA) content and doubling of long-chain acylcarnitine (C14-C18) content in response to HFL and HFP feeding were accompanied by increase in protein levels of peroxisome proliferator-activated receptor-γ coactivator-1α, mitochondrial oxidative phosphorylation complexes and acyl-CoA dehydrogenases involved in mitochondrial FA β-oxidation. Peak force of FT EDL twitch and tetanic contractions was unaltered, but the relaxation time (RT) of twitch contractions was 30% slower compared to LFD controls. The latter was caused by accumulation of lipid intermediates rather than changes in the expression levels of proteins involved in calcium handling. In ST soleus muscle, no evidence for lipid overload was found in any HFD group. However, particularly in HFP group, the peak force of twitch and tetanic contractions was reduced, but RT was faster than LFD controls. The latter was associated with a fast-to-slow shift in troponin T isoform expression. Taken together, these data highlight fiber-type-specific sensitivities and phenotypic adaptations to dietary lipid overload that differentially impact fast- versus slow-twitch skeletal muscle contractile function. © 2015 Elsevier Inc.
De Jong J.,Netherlands Cancer Institute |
De Ridder J.,Netherlands Cancer Institute |
De Ridder J.,Technical University of Delft |
Van Der Weyden L.,Wellcome Trust Sanger Institute |
And 10 more authors.
Nucleic Acids Research | Year: 2011
Insertional mutagenesis is a potent forward genetic screening technique used to identify candidate cancer genes in mouse model systems. An important, yet unresolved issue in the analysis of these screens, is the identification of the genes affected by the insertions. To address this, we developed Kernel Convolved Rule Based Mapping (KC-RBM). KC-RBM exploits distance, orientation and insertion density across tumors to automatically map integration sites to target genes. We perform the first genome-wide evaluation of the association of insertion occurrences with aberrant gene expression of the predicted targets in both retroviral and transposon data sets. We demonstrate the efficiency of KC-RBM by showing its superior performance over existing approaches in recovering true positives from a list of independently, manually curated cancer genes. The results of this work will significantly enhance the accuracy and speed of cancer gene discovery in forward genetic screens. KC-RBM is available as R-package. © 2011 The Author(s).
Van Beek J.H.G.M.,VU University Amsterdam |
Supandi F.,VU University Amsterdam |
Gavai A.K.,Netherlands Consortium for Systems Biology |
Gavai A.K.,VU University Amsterdam |
And 4 more authors.
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences | Year: 2011
The human physiological system is stressed to its limits during endurance sports competition events.We describe a whole body computational model for energy conversion during bicycle racing. About 23 per cent of the metabolic energy is used for muscle work, the rest is converted to heat. We calculated heat transfer by conduction and blood flow inside the body, and heat transfer from the skin by radiation, convection and sweat evaporation, resulting in temperature changes in 25 body compartments. We simulated a mountain time trial to Alpe d'Huez during the Tour de France. To approach the time realized by Lance Armstrong in 2004, very high oxygen uptake must be sustained by the simulated cyclist. Temperature was predicted to reach 39°C in the brain, and 39.7°C in leg muscle. In addition to the macroscopic simulation, we analysed the buffering of bursts of high adenosine triphosphate hydrolysis by creatine kinase during cyclical muscle activity at the biochemical pathway level. To investigate the low oxygen to carbohydrate ratio for the brain, which takes up lactate during exercise, we calculated the flux distribution in cerebral energy metabolism. Computational modelling of the human body, describing heat exchange and energy metabolism, makes simulation of endurance sports events feasible. This journal is © 2011 The Royal Society.
Lange K.,Wageningen University |
Hugenholtz F.,Wageningen University |
Jonathan M.C.,Wageningen University |
Schols H.A.,Wageningen University |
And 6 more authors.
Molecular Nutrition and Food Research | Year: 2015
Scope: The aim of our study was to investigate and compare the effects of five fibers on the mucosal transcriptome, together with alterations in the luminal microbiota composition and SCFA concentrations in the colon. Methods and results: Mice were fed fibers that differed in carbohydrate composition or a control diet for 10 days. Colonic gene expression profiles and luminal microbiota composition were determined by microarray techniques, and integrated using multivariate statistics. Our data showed a distinct reaction of the host and microbiota to resistant starch, a fiber that was not completely fermented in the colon, whereas the other fibers induced similar responses on gene expression and microbiota. Consistent associations were revealed between fiber-induced enrichment of Clostridium cluster IV and XIVa representatives, and changes in mucosal expression of genes related to energy metabolism. The nuclear receptor PPAR-γ was predicted to be an important regulator of the mucosal responses. Conclusion: Results of this exploratory study suggest that despite different sources and composition, fermentable fibers induce a highly similar mucosal response that may at least be partially governed by PPAR-γ. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Schmitz J.P.J.,TU Eindhoven |
Vanlier J.,TU Eindhoven |
van Riel N.A.W.,TU Eindhoven |
Jeneson J.A.L.,Netherlands Consortium for Systems Biology |
And 2 more authors.
Critical Reviews in Biomedical Engineering | Year: 2011
Mitochondria are the power plant of the heart, burning fat and sugars to supply the muscle with the adenosine triphosphate (ATP) free energy that drives contraction and relaxation during each heart beat. This function was first captured in a mathematical model in 1967. Today, interest in such a model has been rekindled by ongoing in silico integrative physiology efforts such as the Cardiac Physiome project. Here, the status of the field of computational modeling of mitochondrial ATP synthetic function is reviewed. © 2011 by Begell House, Inc.
Astola L.,Wageningen University |
Stigter H.,Wageningen University |
Van Dijk A.D.J.,Wageningen University |
Van Daelen R.,Netherlands Consortium for Systems Biology |
And 2 more authors.
PLoS ONE | Year: 2014
The architecture of tomato inflorescence strongly affects flower production and subsequent crop yield. To understand the genetic activities involved, insight into the underlying network of genes that initiate and control the sympodial growth in the tomato is essential. In this paper, we show how the structure of this network can be derived from available data of the expressions of the involved genes. Our approach starts from employing biological expert knowledge to select the most probable gene candidates behind branching behavior. To find how these genes interact, we develop a stepwise procedure for computational inference of the network structure. Our data consists of expression levels from primary shoot meristems, measured at different developmental stages on three different genotypes of tomato. With the network inferred by our algorithm, we can explain the dynamics corresponding to all three genotypes simultaneously, despite their apparent dissimilarities. We also correctly predict the chronological order of expression peaks for the main hubs in the network. Based on the inferred network, using optimal experimental design criteria, we are able to suggest an informative set of experiments for further investigation of the mechanisms underlying branching behavior. © 2014 Astola et al.
PubMed | Wageningen University and Netherlands Consortium for Systems Biology
Type: Comparative Study | Journal: Molecular nutrition & food research | Year: 2015
The aim of our study was to investigate and compare the effects of five fibers on the mucosal transcriptome, together with alterations in the luminal microbiota composition and SCFA concentrations in the colon.Mice were fed fibers that differed in carbohydrate composition or a control diet for 10 days. Colonic gene expression profiles and luminal microbiota composition were determined by microarray techniques, and integrated using multivariate statistics. Our data showed a distinct reaction of the host and microbiota to resistant starch, a fiber that was not completely fermented in the colon, whereas the other fibers induced similar responses on gene expression and microbiota. Consistent associations were revealed between fiber-induced enrichment of Clostridium cluster IV and XIVa representatives, and changes in mucosal expression of genes related to energy metabolism. The nuclear receptor PPAR- was predicted to be an important regulator of the mucosal responses.Results of this exploratory study suggest that despite different sources and composition, fermentable fibers induce a highly similar mucosal response that may at least be partially governed by PPAR-.